Feeds:
Posts
Comments

Posts Tagged ‘Nanotech/Materials Science’


Nano-guided cell networks as conveyors of molecular communication

Nature Communications
6,
Article number:
8500
doi:10.1038/ncomms9500
Received
07 March 2015
Accepted
28 August 2015
Published
12 October 2015

Abstract

Advances in nanotechnology have provided unprecedented physical means to sample molecular space. Living cells provide additional capability in that they identify molecules within complex environments and actuate function. We have merged cells with nanotechnology for an integrated molecular processing network. Here we show that an engineered cell consortium autonomously generates feedback to chemical cues. Moreover, abiotic components are readily assembled onto cells, enabling amplified and ‘binned’ responses. Specifically, engineered cell populations are triggered by a quorum sensing (QS) signal molecule, autoinducer-2, to express surface-displayed fusions consisting of a fluorescent marker and an affinity peptide. The latter provides means for attaching magnetic nanoparticles to fluorescently activated subpopulations for coalescence into colour-indexed output. The resultant nano-guided cell network assesses QS activity and conveys molecular information as a ‘bio-litmus’ in a manner read by simple optical means.

At a glance

Figures

View all figures

left

  1. Nano-guided cell networks for processing molecular information.
    Figure 1
  2. Cells express functional, interchangeable protein components indicating both fluorescence and ability for streptavidin-linked surface coupling.
    Figure 2
  3. Cells equipped with magnetic nanoparticles (mNPs) via streptavidin-mediated interaction with surface-expressed proteins.
    Figure 3
  4. Affinity-based probing for functional analysis of AI-2-induced protein expression.
    Figure 4
  5. Single and multi-population cell responses to autoinducer-2.
    Figure 5
  6. Binning molecular information through cell-based parallel processing and magnetically focusing fluorescence into collective consensus output.
    Figure 6
  7. Extension of nano-guided cell networks for hypothetical regulatory structures.
    Figure 7

right

Introduction

It has become increasingly apparent that a wealth of molecular information exists, which, when appropriately accessed, can provide feedback on biological systems, their componentry and their function. Thus, there is a developing niche that transcends length scales to concurrently recognize molecular detail and at the same time provide understanding of the overall system1, 2. An emerging scheme is to develop nano- to micro-scaled tools that intimately engage with biological systems through monitoring and interacting at the molecular level, with synthetic biology being one such tool3, 4, 5, 6, 7.

While synthetic biology is often viewed as an innovative means for ‘green’ product synthesis through the genetic rearrangement of cells, their biosynthetic capabilities and their regulatory networks can instead be tuned for executive function8, 9, 10. That is, cells can be rewired to survey molecular space3, 11, 12 as they have sophisticated capabilities to recognize, amplify and transduce chemical information13. Further, they provide a means to connect biological systems with traditional microelectronic devices and in doing so present a potential interface between chemically based biomolecular processing and conventional vectors of information flow, such as electrons and photons14, 15, 16. Specifically, through engineered design, cell-based molecular processing can be further coupled to enable external abiotic responses. Cells, then, represent a versatile means for mediating the molecular ‘signatures’ common in complex environments, or in other words, they are conveyors of molecular communication17, 18, 19.

Further, beyond clonal cell-based sensors, there is an emerging concept of population engineering to establish microorganisms in deliberate networks that enable enriched system identification through a combination of distinctive yet coexistent behaviours, including, perhaps, competitive or cooperative features8, 20, 21, 22, 23, 24, 25. We posit the use of cell populations assembled in parallel¸ where multiple microbes with distinct molecular recognition capabilities work congruently. An advantage is that populations, as opposed to few cells, can facilitate thorough sampling since the presence of many cells increases their spatial breadth and per-cell data contributions (Fig. 1a). Each cellular unit undergoes independent decision-making and contributes a datum to its entire constituency. The prevalence of data provided within the population, then, substantiates a collective output by the system based on the molecular landscape. As follows in a multi-population system, molecular input thus influences the outcomes of each population, and elicits plural responses when the molecular input ranges overlap the ranges of the sensing populations21, which can define classification boundaries (Fig. 1a). Cell-mediated classification was posited in silico by Didovyk et al.21, where reporter libraries with randomized sensitivities to a molecular cue elicit concentration-dependent fluorescent patterns and these are elucidated by population screening . In the present construct, multiple populations enable multiplexed analysis, resulting, here, in a response gradation that is designed to index the molecular input ‘signature’. Consequently, the fed-back information becomes transfigured beyond a dose-dependent cell-by-cell analysis. That is, the output is predicated by the comparison between the populations rather than accumulation of response within a total population.

Figure 1: Nano-guided cell networks for processing molecular information.

Nano-guided cell networks for processing molecular information.

(a) Biotic (multicellular) processing is facilitated by cell recognition, signal transduction and genetic response. The genetically encoded response reflects the identity and prevalence of the target molecule(s). Biotic processing includes both increased cell number of responders and their genetically tuned response patterns. (b) Abiotic processing, used in conjunction with biotic processing, adds dimensionality to cell-based output by modifying through a physical stimulus (in our example, magnetic focusing). (c) Schematic of a cell population and nanomaterial-based network comprising both biotic (green/red axis) and abiotic (black axis) processing mechanisms. This conceptual system interprets molecular information by intercepting diverse molecular inputs, processes them autonomously through independent cell units within the system and refines output to include positive responders that are viewed via orthogonal means (visual classification). The system’s hierarchical structure allows molecular information to be refined into categorized collective outputs.

With population engineering as a premise for enriched molecular information processing, we engineered cell species, each to achieve an appropriate output through genetic means. There is conceptual basis for incorporation into networks, such as through mobile surveillance and position-based information relay26, 27. Hence, it is conceivable that, in addition to autonomous molecular recognition and processing afforded by synthetic biology, the use of physical stimuli to enable cell response could confer similar networking properties28, 29. For example, the complete information-processing ‘repertoire’ can be expanded beyond specific cell responses by the integration of external stimuli that serve to collate cell populations30. Specifically, we envision integration of nanomaterials that enable co-responses to molecular inputs, such that cell populations employ traditional reporting functions, that is, fluorescence marker expression, as well as responses that enable additional processing via the integration of stimuli-responsive abiotic materials (Fig. 1b).

In our example, cells are engineered to respond by permitting the attachment of magnetic nanoparticles (mNPs), such that each fluorescent cell becomes receptive to a magnetic field. Thus, the combination of cell-nanoparticle structures provides further dimensionality for the conveyance of molecular information (via magnetic stimulation). That is, without magnetic collation the fully distributed system would harbour diffuse responses; a magnetically stimulated system results in acute output due to a filtering and focusing effect (Fig. 1b)31, 32, allowing binned information to be readily, and fluorescently, conveyed.

The detection and interpretation of signalling molecules in our example is based on a microbial communication process known as quorum sensing (QS). The molecules, autoinducers (AIs), are secreted and perceived within a microbial community; once accumulated, the AI level indicates that the population size has reached a ‘quorum’33, 34. By surpassing a threshold concentration, the AI signalling coordinates population-wide phenotypic changes35. We have designed a QS information processor that utilizes two cell populations to independently interrogate natural microbial communities and generate information about QS activity by accessing AI-2 (ref. 36). Each cell population becomes ‘activated’ in response to a characteristic AI-2 level by expressing a fluorescent marker and a streptavidin-binding peptide (SBP) on the outer membrane38. SBP provides a means for collating data by binding mNPs that are introduced into the community. Using a post-processing magnetic sweep, the system as a whole interprets a molecular landscape and refines output into colour-categorized, or ‘binned,’ states (no fluorescence, red, or red and green) through (1) parallel population processing and (2) acute focusing (Fig. 1c).

The use of engineered cells as data-acquiring units and selectively equipping each with functional nanomaterials to form a redistributable processing system merges two paradigms: decentralized, active probing at a molecular scale and self-organization of units through structured dependencies on stimuli42. The population-based system overall contributes categorized feedback about a biological environment.

Results

Surface expression of SBP and fluorescent protein fusions

First, we established expression of a fusion protein consisting of a fluorescent marker (enhanced green fluorescent protein (eGFP) and variants) and SBP. Importantly, for SBP to function as a coupling agent between cells and mNPs, we used AIDAc (kindly shared by J. Larssen)40 to export the chimeric protein to Escherichia coli’s outer surface. Translocation to a cell’s surface utilizes a signal peptide (for inner membrane translocation) and AIDAc as an outer membrane autotransporter pore38, 39, 40, 41, with the passenger protein linked to each. In Fig. 2a, we depict expression of three different constructs using Venus, eGFP and mCherry for optical transmission, and the AIDAc translocator domain for surface localization. These constructs are mapped inSupplementary Fig. 1. After induction with isopropyl B-D-1-thiogalactopyranoside (IPTG), cultures were probed for surface expression of the SBP portion of the tagged fluorescent protein. Cells were incubated with fluorescently labelled streptavidin; the fluorophore of the streptavidin probe was orthogonal to the expressed fluorescent protein. The multiple fluorescence emissions were analysed by confocal microscopy without spectral overlap. The fraction of cells (fc) that exhibit colocalized fluorescent protein and the fluorescently-labeled streptavidin is reported in Fig. 2b, showing that SBP–Venus cells bound streptavidin at a slightly lower frequency than SBP–mCherry and SBP–eGFP, which exhibited statistically similar fractions (fc=0.7).

Figure 2: Cells express functional, interchangeable protein components indicating both fluorescence and ability for streptavidin-linked surface coupling.

Cells express functional, interchangeable protein components indicating both fluorescence and ability for streptavidin-linked surface coupling.

(a) A T7 cassette was used to express chimeric proteins consisting of a membrane autotransporter domain (AIDAc), one of several fluorescent proteins and a streptavidin-binding peptide (SBP). Fluorophore-tagged streptavidin (SA) was used to bind SBP. (b) Of cells expressing fluorescent proteins (FP), those also marked by SBP coupling are represented as a ‘colocalized fraction (fc),’ plotted with image analysis-based s.d. of at least five replicates. The asterisk ‘*’ denotes fc that +SBP–eGFP and+SBP–mCherry are statistically equivalent (fc~0.7) by t-test and greater than +SBP–Venus cells. (c) Composite images show cell fluorescence (Column I) from the fluorescent protein (FP); labelled streptavidin using orthogonal filter sets (Column II); and an overlay of both (Column III). Arrows indicate representative cells with strong colocalization. Plotted in Column IV are the fluorescence mean grey values (y-axis) from a representative horizontal slice of the composite image (x-axis). Vertical bars displayed between Columns III and IV identify the position of each analysed slice. Arrows indicate peaks that match the highlighted cells in Column III. fc values are noted. Fluorophores with non-overlapping spectra were paired. Row 1, Venus expression (yellow-green) was paired with Dylight405-labelled SA (blue). Row 2, eGFP expression (green) was paired with Alexafluor594-labeled SA (red). Row 3, mCherry expression (red) was paired with Alexafluor488-labeled SA (green). Scale bar in lower left, 50μm.

That is, microscopy results related to the colocalization analysis are depicted for pairings of Venus and blue-streptavidin (SA), eGFP and red-SA, and mCherry and green-SA (Fig. 2c). Strong signals were observed in both filter sets (the fluorescent protein (Column I) and the labelled streptavidin (Column II)). Overlaying each image reveals colocalization, as indicated in Column III, where arrows point to examples of strong colocalization. In addition, Column IV plots fluorescence intensities across horizontal sections of the images, where cells that exhibit colocalized fluorescence are indicated by superimposed peaks. For +pSBP–Venus cells, those with both a blue and yellow signal are observed as pale blue–violet in the overlaid image. Cells with +pSBP–eGFP and +pSBP–mCherry and labelled streptavidin emit both green and red signals; their colocalization appears yellow. Controls shown in Supplementary Fig. 2, verify that fluorescent streptavidin (all colours) has specificity for only SBP-expressing cells over negative controls. Colocalization indicates that not only are both components of the fusion, SBP and the fluorescent protein, expressed, but that SBP is accessible to bind streptavidin on the cell’s surface. This is the first use of AIDAc for cell surface anchoring of fluorescent proteins, each having been functionalized with an affinity peptide.

Cell hybridization via mNPs

Given that expression of a fluorescent protein tagged with SBP enabled external binding of streptavidin, we employed this interaction for fastening streptavidin-functionalized materials directly to the cell surface. We chose streptavidin-conjugated mNPs, 100nm in diameter (an order of magnitude smaller than a cell), for binding to a cell surface (Fig. 3a) to impart the abiotic magnetic properties. Scanning electron microscopy (SEM) was used to observe surface interaction between cell surface-expressing SBP and streptavidin-functionalized mNPs. Supplementary Fig. 3a,bshows electron micrographs of E. coli cells (dimensions 1.5–2μm in length) and the mNPs (~100nm in diameter). The SEM image in Fig. 3b, shows a magnetically isolated SBP-expressing cell with streptavidin-mNPs. The sample was prepared by mixing SBP-expressing cells with streptavidin-mNPs, then collecting or ‘focusing’ into a magnetized pellet via magnetic field, then separating from unbound cells in the supernatant. The cells were then washed and resuspended. In Fig. 3b, clusters of surface-bound mNPs are observed. In addition, the elemental composition was analysed with energy-dispersive X-ray spectroscopy, shown in Fig. 3c by an element map superimposed with carbon (red) and iron (green). While the cell appears to be of a uniform carbon composition, the particles localized at the cell surface (highlighted with arrows) were found having a strong iron composition; thus, elemental analysis confirmed particle identity as iron oxide mNPs. Additional characterization of magnetic functionality, including detailed SEM and fluorescent microscopic analysis prior to and after application of magnetic fields, is described in theSupplementary Information (Supplementary Fig. 3).

Figure 3: Cells equipped with magnetic nanoparticles (mNPs) via streptavidin-mediated interaction with surface-expressed proteins.

Cells equipped with magnetic nanoparticles (mNPs) via streptavidin-mediated interaction with surface-expressed proteins.

(a) Cell surface binding of streptavidin-conjugated magnetic nanoparticles occurs via surface-anchored streptavidin-binding peptide (SBP). The fusion of T7-expressed SBP-fluorescent protein (FP)-AIDAc enables the cell surface accessibility. (b) Scanning electron micrograph of an E. coli cell with surface-bound particles. (c) Element map of carbon (red) and iron (green) through energy-dispersive spectroscopy.

In sum, the well-known affinity interaction between streptavidin and the peptide SBP is harnessed to endow cells with non-natural abiotic properties. Here coupling a functionalized nanomaterial to the surface-displayed peptide physically extends the fusion protein and also adds physical (magnetic) functionality to the cell.

Linking expression to AI-2 recognition

The expression system for pSBP–Venus was then put under AI-2 control so that the protein is expressed in the presence of AI-2 instead of IPTG. That is, we coupled the native QS signal transduction circuitry to the reporter cassette. To ensure ample expression (as the native operon is fairly weak), we placed expression of T7 RNA polymerase under control of the natural QS circuitry43. Phosphorylated AI-2 activates the system through derepression of the regulator LsrR, naturally upregulating AI-2 import and phosphorylation44, and, by design, the T7 RNA polymerase on a sensor plasmid43. When sbp–Venus is included downstream of a T7 promoter region on a second plasmid, expression is then triggered by AI-2 uptake (Supplementary Fig. 4a). Then, we used two host sensor strains engineered to provide varied AI-2 sensitivity (denoted responders ‘A’ and ‘B’). In ‘A’, lsrFG, genes required for internally phosphorylated AI-2 degradation45, 46 are deleted. Also, both strains lack the terminal AI-2 synthase, luxS, so they cannot produce AI-2 and, instead, must ‘receive’ AI-2 from an external source (Supplementary Fig. 4a). The phenotypic difference between A and B is the threshold level of AI-2 that activates the genetic response47, 48. Fully constructed, these cells are designed to take up and process AI-2 to generate fluorescence output (that co-functions with streptavidin binding).

We next evaluated the kinetics of surface-fusion protein expression and effects on cell growth. The AI-2-induced expression for AIDAc-linked and SBP-tagged fluorescent proteins did not alter growth kinetics for either cell type (Supplementary Fig. 4b,c). Expression efficacy was also evaluated via immunoassay of the outer membrane, probing for AI-2-induced surface display. After induction with 20μM AI-2, extracts from cell types A and B were size-separated and blotted using alkaline phosphatase-conjugated streptavidin to probe for the SBP-tagged protein fusion (Supplementary Fig. 5). The 88kDa AIDAc–Venus–SBP protein was only found in the membrane-containing pellet fraction (Fig. 4a). Analogously, protein orientation was assessed by immunolabeling the fluorescent protein. Cell type B transformed with pSBP–eGFP was induced with 20μM AI-2 overnight; cell surfaces were then probed for eGFP using a mouse anti-GFP primary antibody and red-labelled secondary anti-mouse IgG. Simultaneously, cells were observed using phase contrast and fluorescence confocal microscopy. We noted a punctate pattern for eGFP, which was in one-to-one correspondence with red immunostaining of the surface-expressed protein. The positive staining of eGFP-expressing cells for red fluorescence, contrasted by the absence of negative control immunostaining indicated surface exposure of the fusion (Supplementary Fig. 6). Confocal microscopy confirmed precise colocalization of the eGFP and red-labelled antibodies within the confines of individual cells (Fig. 4b). Therefore, efficient transport of this functionality to the membrane under AI-2 induction was demonstrated in each host.

Figure 4: Affinity-based probing for functional analysis of AI-2-induced protein expression.

Affinity-based probing for functional analysis of AI-2-induced protein expression.

(a) 64–82kDa region of western blot for pelleted (P) and supernatant (S) protein fractions isolated from Type A and B cells. Alkaline phosphatase-conjugated streptavidin was used to target AIDAc–Venus–SBP at expression timepoints. Arrows indicate the expected position of the full fusion protein. (b) Immunostaining for assessment of the fluorescent protein surface accessibility. The external surfaces of cells expressing AIDAc–eGFP–SBP were probed with an anti–eGFP and Alexafluor594-labelled antibody pair. A representative overlaid fluorescence and phase contrast image is shown along with fluorescence images of the green (G) and red (R) filters for the boxed-in region. Scale bar, 2μM.

Establishing molecular ranges for cell interrogation

Importantly, the engineered cells each provide a characteristic response to the level of AI-2. Recently, we showed that AI-2 level influences the quorum size of responding engineered populations but does not alter the expression level within each quorum47. Here we evaluated our engineered AI-2 responders, again for quorum size (or in other words, percentage of AI-2-responsive cells in the population), this time varying the compositions of molecular input and the configuration of responders (Fig. 5a). First, we added AI-2, synthesized in vitro, to each of the two responder populations (Fig. 5b). We also added conditioned medium (CM), the spent medium from an AI-2 producer culture containing metabolic byproducts, as well as AI-2 (refs 36, 49; Fig. 5c). We also mixed the responder populations and added AI-2 to gauge responses in complex cultures (Fig. 5d).

Figure 5: Single and multi-population cell responses to autoinducer-2.

Single and multi-population cell responses to autoinducer-2.

(a) Fluorescence output is linked to small molecule input, derived from purified or crude sources. Fluorescence from Responders A and B was analysed after exposure to autoinducer-2 (AI-2) in mono and mixed culture environments. (b) Venus expression from in vitro-synthesized AI-2 added to monocultures of A and B. (c) Venus expression from conditioned media (CM) added to monocultures of A and B. CM was isolated from WT W3110 E. coli cultures sampled at indicated OD. Data are averages from triplicate cultures with s.d. indicated. (d) Red and green fluorescence responses to AI-2 during co-incubation of Responders A (pSBP–mCherry+, red) and B (pSBP–eGFP+, green). Representative fluorescence images show colocalization of red and green cells. Scale bar, 10μm. The average cell count per responder cell is plotted against AI-2 concentration, as determined by image analysis in quadruplicate. All data are plotted as averages of at least triplicate samples with s.d.

Specifically, in Fig. 5b, A and B populations were incubated at mid-exponential phase with in vitro-synthesized AI-2 (refs 50, 51) at concentrations: 0, 2, 10, 28 and 75μM. After 12h, samples were observed for fluorescence by confocal microscopy and then quantified by fluorescence-activated cell sorting (FACS; Supplementary Fig. 4c). We found that SBP–Venus expression for responder A cells occurred at the lowest tested level (2μM AI-2), where 56% of the population expressed SBP–Venus and this fraction increased with AI-2 reaching a maximum of 90% at 28μM. For type B, a more gradual trend was found; only ~1% was fluorescent from 0-2μM, and this increased from 9 to 46% as AI-2 was increased to 28μM. Finally, the highest fraction of fluorescing cells was found at the highest concentration tested, 75μM.

We next isolated CM, which contains a dynamic composition of unfiltered metabolites and media components, from W3110 E. coli cultures at intervals during their exponential growth, throughout which AI-2 accumulates (AI-2 levels for the samples are indicated in Supplementary Fig. 7). CM aliquots were mixed with either A or B cells and cultured in triplicate for 12h. Through FACS analysis it was found, again, that a larger subpopulation of A expressed Venus compared with population B at any concentration (Fig. 5c). Statistically relevant expression from B was not apparent until incubated with CM from cultures at an optical density (OD) of 0.23. In all cases, population A recognized AI-2 presence, including from media isolated at a W3110 OD of 0.05, the minimum cell density tested in this study.

The sensitivities of both strains to AI-2-mediated induction corroborate previous literature10, 47. These trends demonstrate that strains engineered for altered sensitivity to molecular cues provide discrimination of concentration level. That is, the identical plasmid expression system was transformed into different hosts, providing robust and distinct levels of expression.

Having developed cell types A and B with differential ability to detect AI-2, we next altered the reporters so that each cell type expressed a unique SBP-fluorescence fusion for colour-coded designation. Cell type A was engineered with pSBP–mCherry and type B with pSBP–eGFP, resulting in red and green fluorescence, respectively. These populations were mixed together in equal proportion at mid-exponential phase, introduced to a range of AI-2 concentrations, and incubated overnight. Populations A and B exhibited equal growth rates when cultured alone and together (Supplementary Fig. 8c); it followed that the cocultures should comprise a 1:1 ratio of each constituent. Fluorescence output is shown by representative images in Fig. 5d. Also in Fig. 5d, the green and red cell count is plotted from a quadruplicate analysis for each input concentration.

Coculturing enables parallel processing as the molecule-rich environment is perceived by each cell, and is processed uniquely per cell type. Yet, since each sensing mechanism is a living and proliferating population, we tested whether the potentially altered dynamics of coculturing would permit the same sensitivities as isolated culturing. We evaluated the Monod-type saturation constant for each population independently and in cocultures. We found, in Fig. 5d, the general trends in response to an increasing AI-2 level were as predicted by modelled response curves (Supplementary Table 4), which were also well-correlated to Fig. 5b data (Supplementary Fig. 8a,b). That is, the saturation constants that describe dependence on AI-2 were unchanged when measured in cocultures. Phenomenologically, as expected, an initial accumulation of red type A responders was found. Then, at higher AI-2 levels, we found an emergence of a green subpopulation (type B). Above 28μM, there was no longer an apparent differential response that would otherwise enable discrimination of AI-2 concentration; based on the consistency with modelled behaviour, coculturing contributed to dampen the response as the maximum percentage of responding cells in cocultures is 50% instead of 100%. However, the overall fluorescence output is enriched by the combination of multiple populations since the ranges of sensitivity overlap and effectively expand that of the master population (Supplementary Fig. 8d). Specifically, because the fluorescence of B is described by a larger saturation constant, its fluorescence continually increases at higher AI-2 concentrations, while the fluorescence of A remains unchanged. Thus, coculturing between A and B enables resolvable output that is lower than the detection limit of B (due to A) yet surpasses the upper limit at which A saturates by the inclusion of B. The choice to fluorescently differentiate A and B was important because the output would otherwise be biased by extracellular components including the existence of non-sensing cells. Due to colour designation of A and B, a colour ‘pattern’ emerges as a feature of the parallel response, which we recognize is independent of the absolute fluorescence of the population.

Consensus feedback through multidimensional processing

We hypothesized that the value of cell-based sensing would be enhanced if the cell output could be collated in an unbiased manner that in turn were easily ‘read’ using optical means. We engaged magnetic processing, which represents an abiotic processing step that enhances the signal by focusing the collective response. Hence, cells were equipped with streptavidin-conjugated mNPs (Fig. 3). The ability of a magnetic field to refine fluorescence output through filtering and focusing is described in the Supplementary Information (Supplementary Fig. 11). Thus, in our combinatorial approach, fluorescence feedback about molecular information within a microbial community entails biotic processing through constituencies of two independent cell types in conjunction with magnetic post-processing that is enabled by guidance at the nanoscale (Fig. 6c). Moreover, since the fluorescence feedback data is provided through two constituencies, consensus from each independently provides an aggregate output; in our example, the output becomes relayed as a distinctive ‘binned’ category due to finite colour-combinations generated from constituencies A and B (Fig. 6c).

Figure 6: Binning molecular information through cell-based parallel processing and magnetically focusing fluorescence into collective consensus output.

Binning molecular information through cell-based parallel processing and magnetically focusing fluorescence into collective consensus output.

(a) A and B cell types were co-incubated with AI-2 levels ranging from 0 to 55μM AI-2 (left axis), then imaged after magnetic nanoparticle coupling and magnetic collation. Fluorescence results (centred directly over the magnet) are shown from high to low input (top left to bottom right). (b) Quantification of red and green fluorescence cell densities per AI-2 level. (c) The process of accessing molecular information begins by distributing Responders A and B within the environment of an AI-2 producer, P. A and B independently express fluorophore fusions and are linked with magnetic nanoparticles on processing autoinducer-2. Magnetic focusing translocates fluorescing responders. Image analysis of the magnetically collated cell aggregate reveals classified fluorescence output, representing the AI-2 composition of the interrogated environment. (d) Bright field (left) and fluorescence (right, red and green filters) images positioned over the edge of a magnet, as indicated by the inset. The sample in the bottom image pair was isolated from an environment of low AI-2 accumulation. The sample in the top image pair was isolated from a high AI-2 environment. (e) Quantification of visual space occupied by collated cells (eGFP and mCherry expressers) while distributed (- magnet) and magnetically focused (+). Scale bars, 50μm.

Again, type A transmits red output (SBP–mCherry+) and type B transmits green (SBP–eGFP+). These were first co-incubated with titred concentrations of AI-2, to obtain results similar to those ofFig. 5d. By coupling mNPs to the responsive parallel populations, we tested for aggregate two-colour output to provide informative feedback within a set of outcomes ranging from no colour, red-only to red+green. After overnight co-incubation and a magnetic sweep with streptavidin-mNPs, fluorescence results are shown in Fig. 6a, where the recovered cells are displayed above a magnet’s center in order from highest to lowest AI-2 level (top left to bottom right). The processing output generated by the range of conditions was quantitatively assessed for contributions from A and B responders. The spatial density of each fluorophore, or the area occupied by fluorescent responders as a percentage of total visible area, was quantified and plotted in Fig. 6b. Here the trend of increasing fluorescence with AI-2 is followed by both A and B cell types; however, red A cells accumulate at a higher rate than green B cells. This relationship between A and B processing is not only consistent with their previous characterizations (Fig. 5) but indicates that the aggregate output is unbiased regardless of assembly with mNPs and magnetic-stimulated redistribution (Supplementary Information, Supplementary Fig. 14a).

Next, A and B cells were added together to probe the QS environment of Listeria innocua, an AI-2-producing cell type that is genetically and ecologically similar to the pathogenic strain L. monocytogenes52. The environment was biased towards low and high cell density conditions by altering nutrient levels to develop contrasting scenarios of AI-2 level. Preliminary characterization in the Supplementary Information indicated that L. innocua proliferation is unperturbed by the presence of E. coli responders (Supplementary Fig. 12) and that type A cells detect AI-2 at lowListeria densities limited by sparse nutrients; then with rich nutrient availability, cell proliferation permits a higher AI-2 level that can be detected by type B (Supplementary Fig. 13). Replicating these conditions, we expected red fluorescence to be observed at low culture density and for green fluorescence to be reported when high (Fig. 6c). Two conditions were tested: L. innocua was proportioned to responder cells at 20:1 in dilute media to establish a low culture density condition or, alternatively, a ratio of 200:1 in rich media for a high culture density condition. After overnight co-incubation and a magnetic sweep (applied directly to the triple strain cultures) with streptavidin-mNPs, the recovered cells are displayed above a magnet’s edge (shown in Fig. 6d). Acute focusing of the fluorescence signals, contributed by each subset population of the processor (A and B), is visually apparent. The magnetic field had a physical effect of repositioning the ‘on’ subsets to be tightly confined within the magnetic field.

The processing output generated by the contrasting culture conditions was again assessed for the respective contributions of A and B, and for changes in spatial signal density due to the magnetic sweep (Fig. 6e). The analysis was based on images provided in Supplementary Fig. 14b. Data inFig. 6e indicate that red type A cells are prevalent regardless of culture condition (except negative controls). However, compared with the low AI-2 condition, the abundance of green cells is 100-fold higher in the high AI-2 condition. In addition, the ratio of green to red was consistent prior to and after magnetic concentration, substantiating observations in the distributed system. Further, data show that magnetic refining increased per-area fluorescence 100-fold or 10-fold in low and high cell culture studies, respectively.

Based on the thresholds established for responder populations A and B, we found colour-coded binning corresponded to AI-2 level, where ‘red-only’ represented less AI-2 than ‘red+green’ (Fig. 5d). Thus, we found a binned output was established via this multidimensional molecular information-processing system and that this matched the expectations. Red feedback (from responder A) indicated dilute AI-2 accumulation occurred in the low density culture. In the dense cultures, high AI-2 accumulation turned on both A and B for combined red and green feedback.

System response patterns defined by parallel populations

Our example demonstrates the concept of an amorphous processing system that utilizes several biotic and abiotic components for multidimensional information processing. Interestingly, a binning effect was enabled: our system yields an index of colour-categorized feedback that characterizes the sampled environment. In Fig. 7, we present a means to extend our approach to multidimensional systems, those with more than one molecule-of-interest and at different concentrations. That is, by appropriate design of the cell responders, we can further enrich the methodology, its depth and breadth of applicability. We depict 10 hypothetical pairs of responses (with defining equations located in Supplementary Table 5)—those that can be driven by appropriately engineering cells to portend altered genetic responses. For example, rows 1 and 3 provide genetic outcomes as a function of analyte (AI-2) concentration. The hypothetical depictions are feasible as ‘designer’ signal transduction and marker expression processes enabled by synthetic biology21, 53, 54. Rows 2 and 4 demonstrate the corresponding visual planes, where red cell numbers (x-axis) are plotted against green (y-axis), illustrated by the first example. If one divides the two-dimensional space into quadrants (no colour, majority red, majority green, and equivalent ratios of red and green), it becomes apparent that the relationship between cell types influences the ‘visual’ or optical output. Thus, the 10 arbitrary response sets yield a variety of pairings that can provide unique visual patterns for categorizing molecular information. We have simplified the analysis by placing dot marker symbols at the various coincident datapoints, revealing visual patterns. In this way, the ability to incorporate unique responses to a multitude of molecular cues, all within a single pair of cells, or through further multiplexing with additional cell populations becomes apparent.

Figure 7: Extension of nano-guided cell networks for hypothetical regulatory structures.

Extension of nano-guided cell networks for hypothetical regulatory structures.

(a) Rows 1 and 3 depict 10 hypothetical genetic responses to molecular inputs for pairs of fluorescence-reporting cell populations (red, R and green, G). Rows 2 and 4 depict genetic responses as phase-plane plots yielding distinct patterns. This establishes a visual field, showing the extent of any population–population bias (illustrated in example case 1). (b) Left panel: a two-population pairing (shown in case 10) defines visual output that inherently bins into three quadrants: Q1, negligible colour; Q2, red bias due to majority red cell output; and Q4, combined red and green output. Right panel: data from Figs 5d and 6bare plotted analogously, where each data point represents an autoinducer-2 input (labelled, μM). As expected, red and green outputs were binned into Q1, Q2 and Q4 as indicated by coloured outlines.

Our AI-2-conveying cell network is similar to example 7 in Fig. 7a and the AI-2 response curves inFig. 5 (characterized by Supplementary Table 4 equations). Example 7 establishes output into three basic quadrants, including Q1 (negligible colour), Q2 (majority red) and Q4 (roughly equal red and green) (Fig. 7b). We recast the data from Figs 5d and 6b as a phase-plane portrait in Fig. 7c. This reveals the mechanisms by which the output is binned and how the originating cell response curves lead to this pattern, which in turn, was unchanged due to magnetic refinement. InSupplementary Fig. 15, we demonstrate a parameterization of the red and green response curves that suggest the methodology is robust, that when cells are appropriately engineered one could ‘tune’ system characteristics to enhance or diminish a binning effect. We suggest that the utility of subcellular genetic tuning extends well beyond per-cell performance. Rather, we suggest such a strategy may be used to guide the dynamics of population architecture for actuation of by-design response patterns at a systems level.

Discussion

While cell-based sensors work well in well-defined assay conditions, extension to complex environments remains a challenge. They grow, they move, they perturb their environs, they report in a time and concentration-dependent manner, small numbers of sensor cells may require signal amplification and so on. Also, increasingly, bacterial cells are engineered for user specified ‘executive’ functions in complex environments55, 56, 57. Their performance depends on their ability to filter out extraneous noise while surveying the molecular landscape, and providing informed actuation.

Our system interrogates the molecular space by focusing on bacterial QS and a widely distributed signal molecule, AI-2. In addition to genetic attributes of the AI-2-responding sensor cells, AI-2 is a chemoattractant for E. coli, and hence E. coli engineered to sense and respond to AI-2 will naturally move towards its sources, enabling full sampling of the prevailing state10, 37. Each strain evaluates AI-2 with a distinct sensitivity. When ‘activated’ in response to a characteristic level, the cells simultaneously expressed a fluorescent marker and a SBP on the outer membrane via AIDAc translocation. SBP provides a means for cell hybridization through its strong affinity to streptavidin, and here, aids in binding mNPs. This enables the non-genetically coded property of cell translocation within a magnetic field through physically stimulated focusing and binning.

By making use of a diversity of biotic and abiotic features, our multidimensional system of ‘responder’ populations exemplifies several key metrics that promote executive performance in such environments: active molecule capture, post-capture refining of the detection output and finally the utilization of multiple feedback thresholds58, 59, 60. Here cells facilitate AI-2 recognition autonomously and actively because, as a distributed network they reside planktonically, chemotaxing to and continually processing signals over time. When AI-2 is detected, a processor cell’s cognate machinery responds by upregulation of the native QS operon, leading to rapid signal uptake and thereby creating an active-capture signal-processing mechanism. To maximize information acquisition and account for a potentially heterogeneous molecular landscape, cells serve as molecular sampling units among a distributed population, which leads to data fed back as a consensus of fluorescent ‘datapoints’. Then, distributed data collection can be selectively reversed via the incorporated abiotic feature: mNPs, fastened externally on the cell through affinity-guided self-assembly. As such, responding cells obtained this extendable feature, thereby becomes sensitized to repositioning within a magnetic field.

The layered nature of the processor here, from the subcellular to multicellular scale, permits a series of selective steps: it commences with the AI-2-triggered expression cascade which releases a tight repressor, surface localization of both the fluorescent protein and SBP tag, and finally nanoparticle binding for recovery. In addition, multiple layers of amplification result in orthogonal fluorescence feedback. The AI-2 detection event leads to whole-cell fluorescence through expression of many protein copies47. Then their physical collection further amplifies the signal, yielding a macroscopic composite of many individual cell units. When utilized as a network of multiple constituencies, responder cell types A and B contribute individual recognition results (off, red or green) to a single consensus output. Finally, due to their overlapping thresholds for recognition of the same molecule, in this case, AI-2, parallel processing by A and B responders can contribute to visual interpretation of information about the molecule. Outcomes are classified into a finite number of states: here output to no fluorescence, red, or red and green, with each addition of colour as a metric of a higher interval of AI-2. In many respects, the elucidation of layered information networks as demonstrated here is analogous to computer information processing via information theory61, 62, 63.

Here, however, interrogation of biological systems requires a reliable means for accessing molecular information—that which is communicated between biological species and that which can be relayed to the end user. The responder cells need not be present in high concentration, nor must they all be collected in the present format. We suggest that engineered biological mechanisms are well-poised to serve at this critical interface between information acquisition and user interaction. Thus, the functional design of components for autonomous self-assembly, decision-making and networking is requisite in the field of micro- and nano-scaled machines. Our combinatorial approach allows for cells to independently assess, yet collectively report, on molecular information. Its processing is enabled through appropriate integration of synthetic biology and nanomaterials design. We suggest this approach provides a rich opportunity to direct many formats of multi-population response through genetic tuning and systems-level engineering. Further development of cellular networks and incorporation of alternate abiotic attributes can expand the depth and breadth of molecular communication for user specified actuation.

Read Full Post »


Cancer detection and therapeutics

Curator: Larry H. Bernstein, MD, FCAP

 

 

Kurzweill Reports

http://kurzweilai.us1.list-manage.com/track/click

Machine learning rivals human skills in cancer detection

Two announcements yesterday (April 21) suggest that deep learning algorithms rival human skills in detecting cancer from ultrasound images and in identifying cancer in pathology reports.

Samsung Medison RS80A ultrasound imaging system (credit: Samsung)

Samsung Medison, a global medical equipment company and an affiliate of Samsung Electronics, has just updated its RS80A ultrasound imaging system with a deep learning algorithm for breast-lesion analysis.

The “S-Detect for Breast” feature uses big data collected from breast-exam cases and recommends whether the selected lesion is benign or malignant. It’s used in in lesion segmentation, characteristic analysis, and assessment processes, providing “more accurate results.”

“We saw a high level of conformity from analyzing and detecting lesion in various cases by using the S-Detect,” said professor Han Boo Kyung, a radiologist at Samsung Medical Center.

“Users can reduce taking unnecessary biopsies and doctors-in-training will likely have more reliable support in accurately detecting malignant and suspicious lesions.”

Deep learning is better than humans in extracting meaning from cancer pathology reports

Meanwhile, researchers from the Regenstrief Institute and Indiana University School of Informatics and Computing at Indiana University-Purdue University Indianapolis say they’ve found that open-source machine learning tools are as good as — or better than — humans in extracting crucial meaning from free-text (unstructured) pathology reports and detecting cancer cases. The computer tools are also faster and less resource-intensive.

(U.S. states require cancer cases to be reported to statewide cancer registries for disease tracking, identification of at-risk populations, and recognition of unusual trends or clusters. This free-text information can be difficult for health officials to interpret, which can further delay health department action, when action is needed.)

“We think that its no longer necessary for humans to spend time reviewing text reports to determine if cancer is present or not,” said study senior author Shaun Grannis*, M.D., M.S., interim director of the Regenstrief Center of Biomedical Informatics.

Awash in oceans of data

“We have come to the point in time that technology can handle this. A human’s time is better spent helping other humans by providing them with better clinical care. Everything — physician practices, health care systems, health information exchanges, insurers, as well as public health departments — are awash in oceans of data. How can we hope to make sense of this deluge of data? Humans can’t do it — but computers can.”

This is especially relevant for underserved nations, where a majority of clinical data is collected in the form of unstructured free text, he said.

The researchers sampled 7,000 free-text pathology reports from over 30 hospitals that participate in the Indiana Health Information Exchange and used open source tools, classification algorithms, and varying feature selection approaches to predict if a report was positive or negative for cancer. The results indicated that a fully automated review yielded results similar or better than those of trained human reviewers, saving both time and money.

Major infrastructure advance

“We found that artificial intelligence was as least as accurate as humans in identifying cancer cases from free-text clinical data. For example the computer ‘learned’ that the word ‘sheet’ or ‘sheets’ signified cancer as ‘sheet’ or ‘sheets of cells’ are used in pathology reports to indicate malignancy.

“This is not an advance in ideas; it’s a major infrastructure advance — we have the technology, we have the data, we have the software from which we saw accurate, rapid review of vast amounts of data without human oversight or supervision.”

The study was published in the April 2016 issue of the Journal of Biomedical Informatics. It was conducted with support from the Centers for Disease Control and Prevention.

Co-authors of the study include researchers at the IU Fairbanks School of Public Health, the IU School of Medicine and the School of Science at IUPUI.

* Grannis, a Regenstrief Institute investigator and an associate professor of family medicine at the IU School of Medicine, is the architect of the Regenstrief syndromic surveillance detector for communicable diseases and led the technical implementation of Indiana’s Public Health Emergency Surveillance System — one of the nation’s largest. Studies over the past decade have shown that this system detects outbreaks of communicable diseases seven to nine days earlier and finds four times as many cases as human reporting while providing more complete data.

Yann Lecun is Director of AI Research, Facebook and a noted deep-learning expert. 

 

Toward better public health reporting using existing off the shelf approaches: A comparison of alternative cancer detection approaches using plaintext medical data and non-dictionary based feature selection

Suranga N. Kasthurirathnea, , Brian E. Dixonb, cJudy GichoyadHuiping XucYuni XiadBurke Mamlinb, dShaun J. Grannisb, d

Highlights

• Cancer cases can be identified in unstructured clinical data to support public health reporting.
• Such cancer detection methods do not require complex external ontologies or human intervention.
• Such approaches can identify cases with sensitivity, specificity, PPV, accuracy, and AUC exceeding 80–90%.
• Automated cancer detection methods perform as well as approaches that require costly clinician input.
• These approaches may be generalized for other health analytics applications and healthcare domains.

Abstract

Objectives

Increased adoption of electronic health records has resulted in increased availability of free text clinical data for secondary use. A variety of approaches to obtain actionable information from unstructured free text data exist. These approaches are resource intensive, inherently complex and rely on structured clinical data and dictionary-based approaches. We sought to evaluate the potential to obtain actionable information from free text pathology reports using routinely available tools and approaches that do not depend on dictionary-based approaches.

Materials and methods

We obtained pathology reports from a large health information exchange and evaluated the capacity to detect cancer cases from these reports using 3 non-dictionary feature selection approaches, 4 feature subset sizes, and 5 clinical decision models: simple logistic regression, naïve bayes, k-nearest neighbor, random forest, and J48 decision tree. The performance of each decision model was evaluated using sensitivity, specificity, accuracy, positive predictive value, and area under the receiver operating characteristics (ROC) curve.

Results

Decision models parameterized using automated, informed, and manual feature selection approaches yielded similar results. Furthermore, non-dictionary classification approaches identified cancer cases present in free text reports with evaluation measures approaching and exceeding 80–90% for most metrics.

Conclusion

Our methods are feasible and practical approaches for extracting substantial information value from free text medical data, and the results suggest that these methods can perform on par, if not better, than existing dictionary-based approaches. Given that public health agencies are often under-resourced and lack the technical capacity for more complex methodologies, these results represent potentially significant value to the public health field.

Graphical abstract
 Image for unlabelled figure

Scientists shoot anticancer drugs deep into tumors

Ultrasonic vibrations cause gas microbubbles to explode, releasing nanoparticles containing anticancer drugs

Schematic of a magnetic microbubble used in the study, containing gas core (blue) and shell of magnetic iron-oxide nanoparticles (red) that form a dense shell (center) around drug-containing nanoparticles. When stimulated by ultrasound at resonant frequencies, the microbubbles explode, releasing the nanoparticles, which can travel hundreds of micrometers into tumor tissue to deliver anticancer drugs and can also be imaged on an MRI machine. (credit: Yu Gao et al./NPG Asia Materials)    http://www.kurzweilai.net/images/magnetic-microbubble.jpg

 

Scientists at Nanyang Technological University (NTU Singapore) have invented a new way to deliver cancer drugs deep into tumor cells.

They created micro-sized gas bubbles coated with anticancer drug particles embedded in iron oxide nanoparticles and used MRI or other magnetic sources to direct these microbubbles to gather around a specific tumor. Then they used ultrasound to vibrate the microbubbles, providing the energy to direct the drug particles into a targeted kill zone in the tumor. The magnetic nanoparticles also allow for imaging in an MRI machine.

The microbubbles were successfully tested in mice and the study has been published by the Nature Publishing Group in Asia Materials.

Overcoming limitations of chemotherapy

This innovative technique was developed by a multidisciplinary team of scientists led by Asst Prof C. J. Xu from the School of Chemical and Biomedical Engineering and Assoc. Prof Claus-Dieter Ohl from the School of Physical and Mathematical Sciences.

Xu, who is also a researcher at the NTU-Northwestern Institute for Nanomedicine, said their new method may solve some of the most pressing problems faced in chemotherapy used to treat cancer.

The main problem is that current chemotherapy drugs cannot be easily targeted. The drug particles flow in the bloodstream, damaging both healthy and cancerous cells. Typically, these drugs are flushed away quickly in organs such as the lungs and liver, limiting their effectiveness.

The remaining drugs are also unable to penetrate deep into the core of the tumor, leaving some cancer cells alive, which could lead to a resurgence in tumor growth.

Delivering anticancer drugs deep into tumors

Schematic of the apparatus used to investigate magnetic microbubble oscillation and nanoparticle release (credit: Yu Gao et al./NPG Asia Materials)
http://www.kurzweilai.net/images/magnetic-microbubble-nanoparticle-release-setup.jpg

The microbubbles are magnetic, so after injecting them into the bloodstream, they can be clustered around the tumor using magnets to ensure that they don’t kill the healthy cells, explains Xu, who has been working on cancer diagnosis and drug delivery systems since 2004.

“More importantly, our invention is the first of its kind that allows drug particles to be directed deep into a tumor in a few milliseconds. They can penetrate a depth of 50 cell layers or more (about 200 micrometers) — twice the width of a human hair. This helps to ensure that the drugs can reach the cancer cells on the surface and also inside the core of the tumor.”

According to Clinical Associate Professor Chia Sing Joo, a Senior Consultant at the Tan Tock Seng Hospital’s Endoscopy Centre and the Urology & Continence Clinic, “For anticancer drugs to achieve their best effectiveness, they need to penetrate into the tumor efficiently in order to reach the cytoplasm of all the cancer cells that are being targeted without affecting the normal cells.

“Currently, this can [only] be achieved by means of a direct injection into the tumor or by administering a large dosage of anticancer drugs, which can be painful, expensive, impractical and might have various side effects. If successful, I envisage [the new drug-delivery system] can be a good alternative treatment in the future, one which is low cost and yet effective for the treatment of cancers involving solid tumors, as it might minimize the side effects of drugs.” Joo is a surgeon experienced in the treatment of prostate, bladder and kidney cancer and a consultant for this study.

According to Ohl, an expert in biophysics who has published previous studies involving drug delivery systems and bubble dynamics, “most prototype drug delivery systems on the market face three main challenges before they can be commercially successful: they have to be non-invasive, patient-friendly, and yet cost-effective. We were able to come up with our solution that addresses these three challenges.”

The 12-person study team included scientists from City University of Hong Kong and Technion – Israel Institute of Technology (Technion). The team plans to use this new drug delivery system in studies on lung and liver cancer using animal models, and eventually clinical studies.

They estimate that it will take another eight to ten years before it reaches human clinical trials.

 

Abstract of Controlled nanoparticle release from stable magnetic microbubble oscillations

Magnetic microbubbles (MMBs) are microbubbles (MBs) coated with magnetic nanoparticles (NPs). MMBs not only maintain the acoustic properties of MBs, but also serve as an important contrast agent for magnetic resonance imaging. Such dual-modality functionality makes MMBs particularly useful for a wide range of biomedical applications, such as localized drug/gene delivery. This article reports the ability of MMBs to release their particle cargo on demand under stable oscillation. When stimulated by ultrasound at resonant frequencies, MMBs of 450 nm to 200 μm oscillate in volume and surface modes. Above an oscillation threshold, NPs are released from the MMB shell and can travel hundreds of micrometers from the surface of the bubble. The migration of NPs from MMBs can be described with a force balance model. With this technology, we deliver doxorubicin-containing poly(lactic-co-glycolic acid) particles across a physiological barrier bothin vitro and in vivo, with a 18-fold and 5-fold increase in NP delivery to the heart tissue of zebrafish and tumor tissue of mouse, respectively. The penetration of released NPs in tissues is also improved. The ability to remotely control the release of NPs from MMBs suggests opportunities for targeted drug delivery through/into tissues that are not easily diffused through or penetrated.

 

 

Artificial protein controls first self-assembly of C60 fullerenes

New discovery expected to lead to new materials with properties such as higher strength, lighter weight, and greater chemical reactivity, resulting in applications ranging from medicine to energy and electronics
Buckminsterfullerene (C60), aka fullerene and buckyball (credit: St Stev via Foter.com / CC BY-NC-ND)   http://www.kurzweilai.net/images/Dartmouth-Artificial-Protein-Study.jpg

A Dartmouth College scientist and his collaborators* have created the first high-resolution co-assembly between a protein and buckminsterfullerene (C60), aka fullerene and buckyball (a sphere-like molecule composed of 60 carbon atoms and shaped like a soccer ball).

“This is a proof-of-principle study demonstrating that proteins can be used as effective vehicles for organizing nanomaterials by design,” says senior author Gevorg Grigoryan, an assistant professor of computer science at Dartmouth and senior author of a study discussed in an open-access paper in the journal in Nature Communications.

Proteins organize and orchestrate essentially all molecular processes in our cells. The goal of the new study was to create a new artificial protein that can direct the self-assembly of fullerene into ordered superstructures.

COP, a stable tetramer (a polymer derived from four identical single molecule) in isolation, interacts with C60 (fullerene) molecules via a surface-binding site and further self-assembles into a co-crystalline array called C60Sol–COP (credit: Kook-Han Kim et al./Nature Communications)   http://www.kurzweilai.net/images/self-assembly-with-fullernene.jpg

Grigoryan and his colleagues show that that their artificial protein organizes a fullerene into a lattice called C60Sol–COP. COP, a protein that is a stable tetramer (a polymer derived from four identical single molecules), interacted with fullerene molecules via a surface-binding site and further self-assembled into an ordered crystalline superstructure. Interestingly, the superstructure exhibits high charge conductance, whereas both the protein-alone crystal and amorphous C60 are electrically insulating.

Grigoryan says that if we learn to do the programmable self-assembly of precisely organized molecular building blocks more generally, it will lead to a range of new materials with properties such as higher strength, lighter weight, and greater chemical reactivity, resulting in a host of applications, from medicine to energy and electronics.

Fullerenes are currently used in nanotechnology because of their high heat resistance and electrical superconductivity (when doped), but the molecule has been difficult to organize in useful ways.

* The study also included researchers from Dartmouth College, Sungkyunkwan University, the New Jersey Institute of Technology, the National Institute of Science Education and Research, the University of California-San Francisco, the University of Pennsylvania, and the Institute for Basic Science.

Abstract of Protein-directed self-assembly of a fullerene crystal

Learning to engineer self-assembly would enable the precise organization of molecules by design to create matter with tailored properties. Here we demonstrate that proteins can direct the self-assembly of buckminsterfullerene (C60) into ordered superstructures. A previously engineered tetrameric helical bundle binds C60 in solution, rendering it water soluble. Two tetramers associate with one C60, promoting further organization revealed in a 1.67-Å crystal structure. Fullerene groups occupy periodic lattice sites, sandwiched between two Tyr residues from adjacent tetramers. Strikingly, the assembly exhibits high charge conductance, whereas both the protein-alone crystal and amorphous C60 are electrically insulating. The affinity of C60 for its crystal-binding site is estimated to be in the nanomolar range, with lattices of known protein crystals geometrically compatible with incorporating the motif. Taken together, these findings suggest a new means of organizing fullerene molecules into a rich variety of lattices to generate new properties by design.

 

Protein-directed self-assembly of a fullerene crystal

Kook-Han KimDong-Kyun KoYong-Tae KimNam Hyeong Kim,….., Yong Ho Kim Gevorg Grigoryan
Nature Communications 2016;7,(11429)
               http://www.nature.com/ncomms/2016/160426/ncomms11429/full/ncomms11429.html

Programmable self-assembly of molecular building blocks is a highly desirable way of achieving bottom-up control over novel functions and materials. Applications of molecular assemblies are well explored in the literature, ranging from optoelectronic1, 2, magnetic3, and photovoltaic4 devices to chemical and bioanalytical sensing5, and medicine6. However, it has been a daunting challenge to quantitatively describe and control the driving forces that govern self-assembly, particularly given the broad range of molecular building blocks one would like to organize. In this respect, nature’s self-assembling macromolecules hold considerable promise as standard chassis for encoding precise organization. By learning to engineer the assembly of these molecules, myriad other molecular building blocks can be co-organized in desired ways through non-covalent or covalent attachment. The protein polymer is a particularly attractive candidate for a standard assembly chassis given its rich chemical alphabet, diversity of available assembly geometries, broad ability to engage other molecular moieties, and the possibility of engineered function. Considerable progress has been made in the area of engineering protein assemblies7, 8, using either computational9, 10,11, 12, 13, 14 or rational approaches15, 16, 17, 18, but the problem remains a grand challenge. A major difficulty lies in accounting for the enormous continuum of possible assembly geometries available to proteins to engineer a sequence that predictably prefers just one. General design principles, which provide predictive rules of assembly, are thus of enormous utility in limiting the geometric search space and enabling robust design11, 19.

In this work, we demonstrate the first ever high-resolution structure of co-assembly between a protein and buckminsterfullerene (C60), which suggests a simple structural mode for protein–fullerene co-organization. Three separate crystal structures, resolved to 1.67, 1.76 and 2.35Å, reveal a protein lattice with C60 groups occupying periodic sites wedged between two helical segments, each donating a Tyr residue. A half site of the motif is estimated to have nM-scale affinity for C60, such that binding of fullerene appears to direct the organization of protein units in the co-crystal. The assembly exhibits a nm-spaced helical arrangement of fullerenes along a crystallographic axis, endowing the crystal with electrical conductance properties. We closely investigate the interfacial geometry of the C60-binding motif, finding it to be common among protein crystal lattices. C60 and its derivatives have been previously reported to interact with several proteins20, 21, 22, 23, 24, 25, although a high-resolution structure of a protein–C60 has been lacking. Still, prior evidence of interaction indicates that fullerenes and proteins are compatible as materials. This, together with the simple (and naturally recurrent) geometry of the C60-binding motif we discover, suggests that it may be possible to use the structural principles emergent from our study to generate a variety of C60–protein co-assemblies to further explore and exploit the properties of fullerenes26.

 

The aim of programmable self-assembly is to anticipate and harness unique collective properties that arise from precisely organized molecular building blocks. To this end, achieving atomic-level precision is crucial. This work demonstrates the first atomic resolution structures of a fullerene–protein assembly, establishing the feasibility of creating such objects, and further suggests a possible design principle for engineering such assemblies in general. How robust the discovered C60-binding motif is towards designing novel assemblies will need to be tested through a number of future design studies. However, the straightforward manner in which self-organization arose in our case, the simplicity of the C60-organizing motif in the lattice, together with its high affinity and the ubiquity of associated interfaces in natural protein lattices, are certainly promising with respect to the general applicability of the design principle. Our work also demonstrates the potential utility of exploring C60/protein co-organization, as derived supercrystals already showed synergistic charge conductance properties. Taken together, these results point to an exciting direction of inquiry towards generating protein–fullerene assemblies for the study and design of novel properties.

 

Scientists turn skin cells into heart and brain cells using only drugs — no stem cells required

Closer to the natural regeneration that happens in animals like newts and salamanders and no medical-safety and embryo concerns
Neurons created from chemically induced neural stem cells. The cells were created from skin cells that were reprogrammed into neural stem cells using a cocktail of only nine chemicals. This is the first time cellular reprogramming has been accomplished without adding external genes to the cells. (credit: Mingliang Zhang, PhD, Gladstone Institutes)   http://www.kurzweilai.net/images/Neurons-Created-From-Chemically-Induced-Neural-Stem-Cells.jpg

Scientists at the Gladstone Institutes have used chemicals to transform skin cells into heart cells and brain cells, instead of adding external genes — making this accomplishment a breakthrough, according to the scientists.

The research lays the groundwork for one day being able to regenerate lost or damaged cells directly with pharmaceutical drugs — a more efficient and reliable method to reprogram cells and one that avoids medical concerns surrounding genetic engineering.

Instead, in two studies published in an open-access paper in Science and in Cell Stem Cell, the team of scientists at the Roddenberry Center for Stem Cell Biology and Medicine at Gladstone used chemical cocktails to gradually coax skin cells to change into organ-specific stem-cell-like cells and ultimately into heart or brain cells.

“This method brings us closer to being able to generate new cells at the site of injury in patients,” said Gladstone senior investigator Sheng Ding, PhD, the senior author on both studies. “Our hope is to one day treat diseases like heart failure or Parkinson’s disease with drugs that help the heart and brain regenerate damaged areas from their own existing tissue cells. This process is much closer to the natural regeneration that happens in animals like newts and salamanders, which has long fascinated us.”

Chemically Repaired Hearts

A human heart cell that was chemically reprogrammed from a human skin cell (credit: Nan Cao/Gladstone Institutes)  http://www.kurzweilai.net/images/chemically-programmed-heart-cell.jpg

Transplanted adult heart cells do not survive or integrate properly into the heart and few stem cells can be coaxed into becoming heart cells.

Instead, in the Science study, the researchers used a cocktail of nine chemicals to change human skin cells into beating heart cells. By trial and error, they found the best combination of chemicals to begin the process by changing the cells into a state resembling multipotent stem cells (cells that can turn into many different types of cells in a particular organ). A second cocktail of chemicals and growth factors then helped transition the cells to become heart muscle cells.

With this method, more than 97% of the cells began beating, a characteristic of fully developed, healthy heart cells. The cells also responded appropriately to hormones, and molecularly, they resembled heart muscle cells, not skin cells. What’s more, when the cells were transplanted into a mouse heart early in the process, they developed into healthy-looking heart muscle cells within the organ.

“The ultimate goal in treating heart failure is a robust, reliable way for the heart to create new muscle cells,” said Srivastava, co-senior author on the Science paper. “Reprogramming a patient’s own cells could provide the safest and most efficient way to regenerate dying or diseased heart muscle.”

Rejuvenating the brain with neural stem cell-like cells

In the second study, authored by Gladstone postdoctoral scholar Mingliang Zhang, PhD, and published in Cell Stem Cell, the scientists created neural stem-cell-like cells from mouse skin cells using a similar approach.

The chemical cocktail again consisted of nine molecules, some of which overlapped with those used in the first study. Over ten days, the cocktail changed the identity of the cells, until all of the skin-cell genes were turned off and the genes of the neural stem-cell-like cells were gradually turned on.

When transplanted into mice, the neural stem-cell-like cells spontaneously developed into the three basic types of brain cells: neurons, oligodendrocytes, and astrocytes. The neural stem-cell-like cells were also able to self-replicate, making them ideal for treating neurodegenerative diseases or brain injury.

With their improved safety, these neural stem-cell-like cells could one day be used for cell replacement therapy in neurodegenerative diseases like Parkinson’s disease and Alzheimer’s disease, according to co-senior author Yadong Huang, MD, PhD, a senior investigator at Gladstone. “In the future, we could even imagine treating patients with a drug cocktail that acts on the brain or spinal cord, rejuvenating cells in the brain in real time.”

 

Gladstone Institutes | Chemically Reprogrammed Beating Heart Cell

Abstract of Conversion of human fibroblasts into functional cardiomyocytes by small molecules

Reprogramming somatic fibroblasts into alternative lineages would provide a promising source of cells for regenerative therapy. However, transdifferentiating human cells to specific homogeneous, functional cell types is challenging. Here we show that cardiomyocyte-like cells can be generated by treating human fibroblasts with a combination of nine compounds (9C). The chemically induced cardiomyocyte-like cells (ciCMs) uniformly contracted and resembled human cardiomyocytes in their transcriptome, epigenetic, and electrophysiological properties. 9C treatment of human fibroblasts resulted in a more open-chromatin conformation at key heart developmental genes, enabling their promoters/enhancers to bind effectors of major cardiogenic signals. When transplanted into infarcted mouse hearts, 9C-treated fibroblasts were efficiently converted to ciCMs. This pharmacological approach for lineage-specific reprogramming may have many important therapeutic implications after further optimization to generate mature cardiac cells.


Abstract of Pharmacological Reprogramming of Fibroblasts into Neural Stem Cells by Signaling-Directed Transcriptional Activation

Cellular reprogramming using chemically defined conditions, without genetic manipulation, is a promising approach for generating clinically relevant cell types for regenerative medicine and drug discovery. However, small-molecule approaches for inducing lineage-specific stem cells from somatic cells across lineage boundaries have been challenging. Here, we report highly efficient reprogramming of mouse fibroblasts into induced neural stem cell-like cells (ciNSLCs) using a cocktail of nine components (M9). The resulting ciNSLCs closely resemble primary neural stem cells molecularly and functionally. Transcriptome analysis revealed that M9 induces a gradual and specific conversion of fibroblasts toward a neural fate. During reprogramming specific transcription factors such as Elk1 and Gli2 that are downstream of M9-induced signaling pathways bind and activate endogenous master neural genes to specify neural identity. Our study provides an effective chemical approach for generating neural stem cells from mouse fibroblasts and reveals mechanistic insights into underlying reprogramming processes.

 

Ultrafast laser technique identifies brain tumors in real time

04/19/2016  Posted by Lee DubayAssociate Editor, BioOptics World

A research group at VU University Amsterdam (The Netherlands) has shown that an ultrafast laser technique can reveal exactly where brain tumors are, producing images in less than a minute and enabling surgeons to removetumors without compromising healthy tissue.

Related: OCT-based approach facilitates brain cancer surgery

Pathologists typically use staining methods, in which chemicals like hematoxylin and eosin turn different tissue components blue and red, revealing its structure and whether there are any tumor cells. But for a definitive diagnosis, this process can take up to 24 hours—which means surgeons may not realize some cancerous tissue has escaped from their attention until after surgery, requiring a second operation and more risk.

But the research team’s new ultrafast laser technique is label-free—instead, they fire short, 20-fs-long laser pulses into the tissue, and when three photons converge at the same time and place, the photons interact with the nonlinear optical properties of the tissue. Through well-known phenomena in optics called second- and third-harmonic generation, these interactions produce a single photon.

The key is that the incoming and outgoing photons have different wavelengths. The incoming photons are at 1200 nm, long enough to penetrate deep into the tissue. The single photon that is produced, however, is at 600 or 400 nm, depending on if it’s second- or third-harmonic generation. The shorter wavelengths mean the photon can scatter in the tissue. The scattered photon thus contains information about the tissue, and when it reaches a detector—in this case, a high-sensitivity gallium arsenide phosphide (GaAsP) photomultiplier tube—it reveals what the tissue looks like inside.

Tissue from a patient diagnosed with low-grade glioma. The green image is taken with the new method, while the pink uses conventional hematoxylin and eosin staining. Going from the upper left to the lower right, both images show increasing cell density because of more tumor tissue. The insets reveal the high density of tumor cells. (Credit: N.V. Kuzmin et al, VU University Amsterdam, The Netherlands)

The research team used the technique to analyze glial brain tumors, which are particularly deadly because it’s hard to get rid of tumor cells by surgery, irradiation, and chemotherapy without substantial collateral damage to the surrounding brain tissue. They tested their method on samples of glial brain tumors from humans, finding that the histological detail in these images was as good—if not better—than those made with conventional staining techniques. They were able to make most images in under a minute. The smaller ones took less than a second, while larger images of a few square millimeters took five minutes—making it possible to do it in real time in the operating room, according to Marloes Groot of VU University Amsterdam, who led the work.

Now that they’ve shown their approach works, the researchers are developing a handheld device that a surgeon can use to identify a tumor’s border during surgery. The incoming laser pulses can only reach a depth of about 100 µm into the tissue. To reach farther, Groot envisions attaching a needle that can pierce the tissue and deliver photons deeper, allowing diagnosis during an operation and possibly before surgery begins.

Full details of the work appear in the journal Biomedical Optics Express; for more information, please visit http://dx.doi.org/10.1364/boe.7.001889.

Third harmonic generation imaging for fast, label-free pathology of human brain tumors

N. V. Kuzmin, P. Wesseling, P. C. de Witt Hamer, D. P. Noske, G. D. Galgano, H. D. Mansvelder, J. C. Baayen, and M. L. Groot
Biomedical Optics Express > Volume 7 > Issue 5 > Page 1889

In brain tumor surgery, recognition of tumor boundaries is key. However, intraoperative assessment of tumor boundaries by the neurosurgeon is difficult. Therefore, there is an urgent need for tools that provide the neurosurgeon with pathological information during the operation. We show that third harmonic generation (THG) microscopy provides label-free, real-time images of histopathological quality; increased cellularity, nuclear pleomorphism, and rarefaction of neuropil in fresh, unstained human brain tissue could be clearly recognized. We further demonstrate THG images taken with a GRIN objective, as a step toward in situ THG microendoscopy of tumor boundaries. THG imaging is thus a promising tool for optical biopsies.

 

 

Read Full Post »


Conduction, graphene, elements and light

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

New 2D material could upstage graphene   Mar 25, 2016

Can function as a conductor or semiconductor, is extremely stable, and uses light, inexpensive earth-abundant elements
http://www.kurzweilai.net/new-2d-material-could-upstage-graphene
The atoms in the new structure are arranged in a hexagonal pattern as in graphene, but that is where the similarity ends. The three elements forming the new material all have different sizes; the bonds connecting the atoms are also different. As a result, the sides of the hexagons formed by these atoms are unequal, unlike in graphene. (credit: Madhu Menon)

A new one-atom-thick flat material made up of silicon, boron, and nitrogen can function as a conductor or semiconductor (unlike graphene) and could upstage graphene and advance digital technology, say scientists at the University of Kentucky, Daimler in Germany, and the Institute for Electronic Structure and Laser (IESL) in Greece.

Reported in Physical Review B, Rapid Communications, the new Si2BN material was discovered in theory (not yet made in the lab). It uses light, inexpensive earth-abundant elements and is extremely stable, a property many other graphene alternatives lack, says University of Kentucky Center for Computational Sciences physicist Madhu Menon, PhD.

Limitations of other 2D semiconducting materials

A search for new 2D semiconducting materials has led researchers to a new class of three-layer materials called transition-metal dichalcogenides (TMDCs). TMDCs are mostly semiconductors and can be made into digital processors with greater efficiency than anything possible with silicon. However, these are much bulkier than graphene and made of materials that are not necessarily earth-abundant and inexpensive.

Other graphene-like materials have been proposed but lack the strengths of the new material. Silicene, for example, does not have a flat surface and eventually forms a 3D surface. Other materials are highly unstable, some only for a few hours at most.

The new Si2BN material is metallic, but by attaching other elements on top of the silicon atoms, its band gap can be changed (from conductor to semiconductor, for example) — a key advantage over graphene for electronics applications and solar-energy conversion.

The presence of silicon also suggests possible seamless integration with current silicon-based technology, allowing the industry to slowly move away from silicon, rather than precipitously, notes Menon.

https://youtu.be/lKc_PbTD5go

Abstract of Prediction of a new graphenelike Si2BN solid

While the possibility to create a single-atom-thick two-dimensional layer from any material remains, only a few such structures have been obtained other than graphene and a monolayer of boron nitride. Here, based upon ab initiotheoretical simulations, we propose a new stable graphenelike single-atomic-layer Si2BN structure that has all of its atoms with sp2 bonding with no out-of-plane buckling. The structure is found to be metallic with a finite density of states at the Fermi level. This structure can be rolled into nanotubes in a manner similar to graphene. Combining first- and second-row elements in the Periodic Table to form a one-atom-thick material that is also flat opens up the possibility for studying new physics beyond graphene. The presence of Si will make the surface more reactive and therefore a promising candidate for hydrogen storage.

 

Nano-enhanced textiles clean themselves with light

Catalytic uses for industrial-scale chemical processes in agrochemicals, pharmaceuticals, and natural products also seen
http://www.kurzweilai.net/nano-enhanced-textiles-clean-themselves-with-light
Close-up of nanostructures grown on cotton textiles. Image magnified 150,000 times. (credit: RMIT University)

Researchers at at RMIT University in Australia have developed a cheap, efficient way to grow special copper- and silver-based nanostructures on textiles that can degrade organic matter when exposed to light.

Don’t throw out your washing machine yet, but the work paves the way toward nano-enhanced textiles that can spontaneously clean themselves of stains and grime simply by being put under a light or worn out in the sun.

The nanostructures absorb visible light (via localized surface plasmon resonance — collective electron-charge oscillations in metallic nanoparticles that are excited by light), generating high-energy (“hot”) electrons that cause the nanostructures to act as catalysts for chemical reactions that degrade organic matter.

Steps involved in fabricating copper- and silver-based cotton fabrics: 1. Sensitize the fabric with tin. 2. Form palladium seeds that act as nucleation (clustering) sites. 3. Grow metallic copper and silver nanoparticles on the surface of the cotton fabric. (credit: Samuel R. Anderson et al./Advanced Materials Interfaces)

The challenge for researchers has been to bring the concept out of the lab by working out how to build these nanostructures on an industrial scale and permanently attach them to textiles. The RMIT team’s novel approach was to grow the nanostructures directly onto the textiles by dipping them into specific solutions, resulting in development of stable nanostructures within 30 minutes.

When exposed to light, it took less than six minutes for some of the nano-enhanced textiles to spontaneously clean themselves.

The research was described in the journal Advanced Materials Interfaces.

Scaling up to industrial levels

Rajesh Ramanathan, a RMIT postdoctoral fellow and co-senior author, said the process also had a variety of applications for catalysis-based industries such as agrochemicals, pharmaceuticals, and natural productsand could be easily scaled up to industrial levels. “The advantage of textiles is they already have a 3D structure, so they are great at absorbing light, which in turn speeds up the process of degrading organic matter,” he said.

Cotton textile fabric with copper-based nanostructures. The image is magnified 200 times. (credit: RMIT University)

“Our next step will be to test our nano-enhanced textiles with organic compounds that could be more relevant to consumers, to see how quickly they can handle common stains like tomato sauce or wine,” Ramanathan said.

“There’s more work to do to before we can start throwing out our washing machines, but this advance lays a strong foundation for the future development of fully self-cleaning textiles.”


Abstract of Robust Nanostructured Silver and Copper Fabrics with Localized Surface Plasmon Resonance Property for Effective Visible Light Induced Reductive Catalysis

Inspired by high porosity, absorbency, wettability, and hierarchical ordering on the micrometer and nanometer scale of cotton fabrics, a facile strategy is developed to coat visible light active metal nanostructures of copper and silver on cotton fabric substrates. The fabrication of nanostructured Ag and Cu onto interwoven threads of a cotton fabric by electroless deposition creates metal nanostructures that show a localized surface plasmon resonance (LSPR) effect. The micro/nanoscale hierarchical ordering of the cotton fabrics allows access to catalytically active sites to participate in heterogeneous catalysis with high efficiency. The ability of metals to absorb visible light through LSPR further enhances the catalytic reaction rates under photoexcitation conditions. Understanding the modes of electron transfer during visible light illumination in Ag@Cotton and Cu@Cotton through electrochemical measurements provides mechanistic evidence on the influence of light in promoting electron transfer during heterogeneous catalysis for the first time. The outcomes presented in this work will be helpful in designing new multifunctional fabrics with the ability to absorb visible light and thereby enhance light-activated catalytic processes.

 

New type of molecular tag makes MRI 10,000 times more sensitive

Could detect biochemical processes in opaque tissue without requiring PET radiation or CT x-rays
http://www.kurzweilai.net/new-type-of-molecular-tag-makes-mri-10000-times-more-sensitive

Duke scientists have discovered a new class of inexpensive, long-lived molecular tags that enhance MRI signals by 10,000 times. To activate the tags, the researchers mix them with a newly developed catalyst (center) and a special form of hydrogen (gray), converting them into long-lived magnetic resonance “lightbulbs” that might be used to track disease metabolism in real time. (credit: Thomas Theis, Duke University)

Duke University researchers have discovered a new form of MRI that’s 10,000 times more sensitive and could record actual biochemical reactions, such as those involved in cancer and heart disease, and in real time.

Let’s review how MRI (magnetic resonance imaging) works: MRI takes advantage of a property called spin, which makes the nuclei in hydrogen atoms act like tiny magnets. By generating a strong magnetic field (such as 3 Tesla) and a series of radio-frequency waves, MRI induces these hydrogen magnets in atoms to broadcast their locations. Since most of the hydrogen atoms in the body are bound up in water, the technique is used in clinical settings to create detailed images of soft tissues like organs (such as the brain), blood vessels, and tumors inside the body.


MRI’s ability to track chemical transformations in the body has been limited by the low sensitivity of the technique. That makes it impossible to detect small numbers of molecules (without using unattainably more massive magnetic fields).

So to take MRI a giant step further in sensitivity, the Duke researchers created a new class of molecular “tags” that can track disease metabolism in real time, and can last for more than an hour, using a technique called hyperpolarization.* These tags are biocompatible and inexpensive to produce, allowing for using existing MRI machines.

“This represents a completely new class of molecules that doesn’t look anything at all like what people thought could be made into MRI tags,” said Warren S. Warren, James B. Duke Professor and Chair of Physics at Duke, and senior author on the study. “We envision it could provide a whole new way to use MRI to learn about the biochemistry of disease.”

Sensitive tissue detection without radiation

The new molecular tags open up a new world for medicine and research by making it possible to detect what’s happening in optically opaque tissue instead of requiring expensive positron emission tomography (PET), which uses a radioactive tracer chemical to look at organs in the body and only works for (typically) about 20 minutes, or CT x-rays, according to the researchers.

This research was reported in the March 25 issue of Science Advances. It was supported by the National Science Foundation, the National Institutes of Health, the Department of Defense Congressionally Directed Medical Research Programs Breast Cancer grant, the Pratt School of Engineering Research Innovation Seed Fund, the Burroughs Wellcome Fellowship, and the Donors of the American Chemical Society Petroleum Research Fund.

* For the past decade, researchers have been developing methods to “hyperpolarize” biologically important molecules. “Hyperpolarization gives them 10,000 times more signal than they would normally have if they had just been magnetized in an ordinary magnetic field,” Warren said. But while promising, Warren says these hyperpolarization techniques face two fundamental problems: incredibly expensive equipment — around 3 million dollars for one machine — and most of these molecular “lightbulbs” burn out in a matter of seconds.

“It’s hard to take an image with an agent that is only visible for seconds, and there are a lot of biological processes you could never hope to see,” said Warren. “We wanted to try to figure out what molecules could give extremely long-lived signals so that you could look at slower processes.”

So the researchers synthesized a series of molecules containing diazarines — a chemical structure composed of two nitrogen atoms bound together in a ring. Diazirines were a promising target for screening because their geometry traps hyperpolarization in a “hidden state” where it cannot relax quickly. Using a simple and inexpensive approach to hyperpolarization called SABRE-SHEATH, in which the molecular tags are mixed with a spin-polarized form of hydrogen and a catalyst, the researchers were able to rapidly hyperpolarize one of the diazirine-containing molecules, greatly enhancing its magnetic resonance signals for over an hour.

The scientists believe their SABRE-SHEATH catalyst could be used to hyperpolarize a wide variety of chemical structures at a fraction of the cost of other methods.


Abstract of Direct and cost-efficient hyperpolarization of long-lived nuclear spin states on universal 15N2-diazirine molecular tags

Abstract of Direct and cost-efficient hyperpolarization of long-lived nuclear spin states on universal 15N2-diazirine molecular tags

Conventional magnetic resonance (MR) faces serious sensitivity limitations, which can be overcome by hyperpolarization methods, but the most common method (dynamic nuclear polarization) is complex and expensive, and applications are limited by short spin lifetimes (typically seconds) of biologically relevant molecules. We use a recently developed method, SABRE-SHEATH, to directly hyperpolarize 15N2 magnetization and long-lived 15N2singlet spin order, with signal decay time constants of 5.8 and 23 min, respectively. We find >10,000-fold enhancements generating detectable nuclear MR signals that last for more than an hour. 15N2-diazirines represent a class of particularly promising and versatile molecular tags, and can be incorporated into a wide range of biomolecules without significantly altering molecular function.

references:

[Seems like they have a great idea, now all they need to do is confirm very specific uses or types of cancers/diseases or other processes they can track or target. Will be interesting to see if they can do more than just see things, maybe they can use this to target and destroy bad things in the body also. Keep up the good work….. this sounds like a game changer.]

 

Scientists time-reverse developed stem cells to make them ‘embryonic’ again

May help avoid ethically controversial use of human embryos for research and support other research goals
http://www.kurzweilai.net/scientists-time-reverse-developed-stem-cells-to-make-them-embryonic-again
Researchers have reversed “primed” (developed) “epiblast” stem cells (top) from early mouse embryos using the drug MM-401, causing the treated cells (bottom) to revert to the original form of the stem cells. (credit: University of Michigan)

University of Michigan Medical School researchers have discovered a way to convert mouse stem cells (taken from an embryo) that have  become “primed” (reached the stage where they can  differentiate, or develop into every specialized cell in the body) to a “naïve” (unspecialized) state by simply adding a drug.

This breakthrough has the potential to one day allow researchers to avoid the ethically controversial use of human embryos left over from infertility treatments. To achieve this breakthrough, the researchers treated the primedembryonic stem cells (“EpiSC”) with a drug called MM-401* (a leukemia drug) for a short period of time.

Embryonic stem cells are able to develop into any type of cell, except those of the placenta (credit: Mike Jones/CC)

…..

* The drug, MM-401, specifically targets epigenetic chemical markers on histones, the protein “spools” that DNA coils around to create structures called chromatin. These epigenetic changes signal the cell’s DNA-reading machinery and tell it where to start uncoiling the chromatin in order to read it.

A gene called Mll1 is responsible for the addition of these epigenetic changes, which are like small chemical tags called methyl groups. Mll1 plays a key role in the uncontrolled explosion of white blood cells in leukemia, which is why researchers developed the drug MM-401 to interfere with this process. But Mll1 also plays a role in cell development and the formation of blood cells and other cells in later-stage embryos.

Stem cells do not turn on the Mll1 gene until they are more developed. The MM-401 drug blocks Mll1’s normal activity in developing cells so the epigenetic chemical markers are missing. These cells are then unable to continue to develop into different types of specialized cells but are still able to revert to healthy naive pluripotent stem cells.


Abstract of MLL1 Inhibition Reprograms Epiblast Stem Cells to Naive Pluripotency

The interconversion between naive and primed pluripotent states is accompanied by drastic epigenetic rearrangements. However, it is unclear whether intrinsic epigenetic events can drive reprogramming to naive pluripotency or if distinct chromatin states are instead simply a reflection of discrete pluripotent states. Here, we show that blocking histone H3K4 methyltransferase MLL1 activity with the small-molecule inhibitor MM-401 reprograms mouse epiblast stem cells (EpiSCs) to naive pluripotency. This reversion is highly efficient and synchronized, with more than 50% of treated EpiSCs exhibiting features of naive embryonic stem cells (ESCs) within 3 days. Reverted ESCs reactivate the silenced X chromosome and contribute to embryos following blastocyst injection, generating germline-competent chimeras. Importantly, blocking MLL1 leads to global redistribution of H3K4me1 at enhancers and represses lineage determinant factors and EpiSC markers, which indirectly regulate ESC transcription circuitry. These findings show that discrete perturbation of H3K4 methylation is sufficient to drive reprogramming to naive pluripotency.


Abstract of Naive Pluripotent Stem Cells Derived Directly from Isolated Cells of the Human Inner Cell Mass

Conventional generation of stem cells from human blastocysts produces a developmentally advanced, or primed, stage of pluripotency. In vitro resetting to a more naive phenotype has been reported. However, whether the reset culture conditions of selective kinase inhibition can enable capture of naive epiblast cells directly from the embryo has not been determined. Here, we show that in these specific conditions individual inner cell mass cells grow into colonies that may then be expanded over multiple passages while retaining a diploid karyotype and naive properties. The cells express hallmark naive pluripotency factors and additionally display features of mitochondrial respiration, global gene expression, and genome-wide hypomethylation distinct from primed cells. They transition through primed pluripotency into somatic lineage differentiation. Collectively these attributes suggest classification as human naive embryonic stem cells. Human counterparts of canonical mouse embryonic stem cells would argue for conservation in the phased progression of pluripotency in mammals.

 

 

How to kill bacteria in seconds using gold nanoparticles and light

March 24, 2016

 

zapping bacteria ft Could treat bacterial infections without using antibiotics, which could help reduce the risk of spreading antibiotics resistance

Researchers at the University of Houston have developed a new technique for killing bacteria in 5 to 25 seconds using highly porous gold nanodisks and light, according to a study published today in Optical Materials Express. The method could one day help hospitals treat some common infections without using antibiotics

Read Full Post »