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A Nonlinear Methodology to Explain Complexity of the Genome and Bioinformatic Information

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A Nonlinear Methodology to Explain Complexity of the Genome and Bioinformatic Information

Reporter: Stephen J. Williams, Ph.D.

Multifractal bioinformatics: A proposal to the nonlinear interpretation of genome

The following is an open access article by Pedro Moreno on a methodology to analyze genetic information across species and in particular, the evolutionary trends of complex genomes, by a nonlinear analytic approach utilizing fractal geometry, coined “Nonlinear Bioinformatics”.  This fractal approach stems from the complex nature of higher eukaryotic genomes including mosaicism, multiple interdispersed  genomic elements such as intronic regions, noncoding regions, and also mobile elements such as transposable elements.  Although seemingly random, there exists a repetitive nature of these elements. Such complexity of DNA regulation, structure and genomic variation is felt best understood by developing algorithms based on fractal analysis, which can best model the regionalized and repetitive variability and structure within complex genomes by elucidating the individual components which contributes to an overall complex structure rather than using a “linear” or “reductionist” approach looking at individual coding regions, which does not take into consideration the aforementioned factors leading to genetic complexity and diversity.

Indeed, many other attempts to describe the complexities of DNA as a fractal geometric pattern have been described.  In a paper by Carlo Cattani “Fractals and Hidden Symmetries in DNA“, Carlo uses fractal analysis to construct a simple geometric pattern of the influenza A virus by modeling the primary sequence of this viral DNA, namely the bases A,G,C, and T. The main conclusions that

fractal shapes and symmetries in DNA sequences and DNA walks have been shown and compared with random and deterministic complex series. DNA sequences are structured in such a way that there exists some fractal behavior which can be observed both on the correlation matrix and on the DNA walks. Wavelet analysis confirms by a symmetrical clustering of wavelet coefficients the existence of scale symmetries.

suggested that, at least, the viral influenza genome structure could be analyzed into its basic components by fractal geometry.

This approach has been used to model the complex nature of cancer as discussed in a 2011 Seminars in Oncology paper

entitled “Fractal analysis in a Systems Biology approach to cancer” by M. Bizzaro et al.

Abstract: Cancer is a highly complex disease due to the disruption of tissue architecture. Thus, tissues, and not individual cells, are the proper level of observation for the study of carcinogenesis. This paradigm shift from a reductionist approach to a systems biology approach is long overdue. Indeed, cell phenotypes are emergent modes arising through collective non-linear interactions among different cellular and microenvironmental components, generally described by “phase space diagrams”, where stable states (attractors) are embedded into a landscape model. Within this framework, cell states and cell transitions are generally conceived as mainly specified by gene-regulatory networks. However, the system s dynamics is not reducible to the integrated functioning of the genome-proteome network alone; the epithelia-stroma interacting system must be taken into consideration in order to give a more comprehensive picture. Given that cell shape represents the spatial geometric configuration acquired as a result of the integrated set of cellular and environmental cues, we posit that fractal-shape parameters represent “omics descriptors of the epithelium-stroma system. Within this framework, function appears to follow form, and not the other way around.

As authors conclude

” Transitions from one phenotype to another are reminiscent of phase transitions observed in physical systems. The description of such transitions could be obtained by a set of morphological, quantitative parameters, like fractal measures. These parameters provide reliable information about system complexity. “

Gene expression also displays a fractal nature. In a Frontiers in Physiology paper by Mahboobeh Ghorbani, Edmond A. Jonckheere and Paul Bogdan^{* “}Gene Expression Is Not Random: Scaling, Long-Range Cross-Dependence, and Fractal Characteristics of Gene Regulatory Networks“,

the authors describe that gene expression networks display time series display fractal and long-range dependence characteristics.

Abstract: Gene expression is a vital process through which cells react to the environment and express functional behavior. Understanding the dynamics of gene expression could prove crucial in unraveling the physical complexities involved in this process. Specifically, understanding the coherent complex structure of transcriptional dynamics is the goal of numerous computational studies aiming to study and finally control cellular processes. Here, we report the scaling properties of gene expression time series in Escherichia coliand Saccharomyces cerevisiae. Unlike previous studies, which report the fractal and long-range dependency of DNA structure, we investigate the individual gene expression dynamics as well as the cross-dependency between them in the context of gene regulatory network. Our results demonstrate that the gene expression time series display fractal and long-range dependence characteristics. In addition, the dynamics between genes and linked transcription factors in gene regulatory networks are also fractal and long-range cross-correlated. The cross-correlation exponents in gene regulatory networks are not unique. The distribution of the cross-correlation exponents of gene regulatory networks for several types of cells can be interpreted as a measure of the complexity of their functional behavior.

 

Given that multitude of complex biomolecular networks and biomolecules can be described by fractal patterns, the development of bioinformatic algorithms  would enhance our understanding of the interdependence and cross funcitonality of these mutiple biological networks, particularly in disease and drug resistance.  The article below by Pedro Moreno describes the development of such bioinformatic algorithms.

Pedro A. Moreno
Escuela de Ingeniería de Sistemas y Computación, Facultad de Ingeniería, Universidad del Valle, Cali, Colombia
E-mail: pedro.moreno@correounivalle.edu.co

Eje temático: Ingeniería de sistemas / System engineering
Recibido: 19 de septiembre de 2012
Aceptado: 16 de diciembre de 2013

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Abstract

The first draft of the human genome (HG) sequence was published in 2001 by two competing consortia. Since then, several structural and functional characteristics for the HG organization have been revealed. Today, more than 2.000 HG have been sequenced and these findings are impacting strongly on the academy and public health. Despite all this, a major bottleneck, called the genome interpretation persists. That is, the lack of a theory that explains the complex puzzles of coding and non-coding features that compose the HG as a whole. Ten years after the HG sequenced, two recent studies, discussed in the multifractal formalism allow proposing a nonlinear theory that helps interpret the structural and functional variation of the genetic information of the genomes. The present review article discusses this new approach, called: “Multifractal bioinformatics”.

Keywords: Omics sciences, bioinformatics, human genome, multifractal analysis.

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1. Introduction

Omic Sciences and Bioinformatics

In order to study the genomes, their life properties and the pathological consequences of impairment, the Human Genome Project (HGP) was created in 1990. Since then, about 500 Gpb (EMBL) represented in thousands of prokaryotic genomes and tens of different eukaryotic genomes have been sequenced (NCBI, 1000 Genomes, ENCODE). Today, Genomics is defined as the set of sciences and technologies dedicated to the comprehensive study of the structure, function and origin of genomes. Several types of genomic have arisen as a result of the expansion and implementation of genomics to the study of the Central Dogma of Molecular Biology (CDMB), Figure 1 (above). The catalog of different types of genomics uses the Latin suffix “-omic” meaning “set of” to mean the new massive approaches of the new omics sciences (Moreno et al, 2009). Given the large amount of genomic information available in the databases and the urgency of its actual interpretation, the balance has begun to lean heavily toward the requirements of bioinformatics infrastructure research laboratories Figure 1 (below).

The bioinformatics or Computational Biology is defined as the application of computer and information technology to the analysis of biological data (Mount, 2004). An interdisciplinary science that requires the use of computing, applied mathematics, statistics, computer science, artificial intelligence, biophysical information, biochemistry, genetics, and molecular biology. Bioinformatics was born from the need to understand the sequences of nucleotide or amino acid symbols that make up DNA and proteins, respectively. These analyzes are made possible by the development of powerful algorithms that predict and reveal an infinity of structural and functional features in genomic sequences, as gene location, discovery of homologies between macromolecules databases (Blast), algorithms for phylogenetic analysis, for the regulatory analysis or the prediction of protein folding, among others. This great development has created a multiplicity of approaches giving rise to new types of Bioinformatics, such as Multifractal Bioinformatics (MFB) that is proposed here.

1.1 Multifractal Bioinformatics and Theoretical Background

MFB is a proposal to analyze information content in genomes and their life properties in a non-linear way. This is part of a specialized sub-discipline called “nonlinear Bioinformatics”, which uses a number of related techniques for the study of nonlinearity (fractal geometry, Hurts exponents, power laws, wavelets, among others.) and applied to the study of biological problems (http://pharmaceuticalintelligence.com/tag/fractal-geometry/). For its application, we must take into account a detailed knowledge of the structure of the genome to be analyzed and an appropriate knowledge of the multifractal analysis.

1.2 From the Worm Genome toward Human Genome

To explore a complex genome such as the HG it is relevant to implement multifractal analysis (MFA) in a simpler genome in order to show its practical utility. For example, the genome of the small nematode Caenorhabditis elegans is an excellent model to learn many extrapolated lessons of complex organisms. Thus, if the MFA explains some of the structural properties in that genome it is expected that this same analysis reveals some similar properties in the HG.

The C. elegans nuclear genome is composed of about 100 Mbp, with six chromosomes distributed into five autosomes and one sex chromosome. The molecular structure of the genome is particularly homogeneous along with the chromosome sequences, due to the presence of several regular features, including large contents of genes and introns of similar sizes. The C. elegans genome has also a regional organization of the chromosomes, mainly because the majority of the repeated sequences are located in the chromosome arms, Figure 2 (left) (C. elegans Sequencing Consortium, 1998). Given these regular and irregular features, the MFA could be an appropriate approach to analyze such distributions.

Meanwhile, the HG sequencing revealed a surprising mosaicism in coding (genes) and noncoding (repetitive DNA) sequences, Figure 2 (right) (Venter et al., 2001). This structure of 6 Gbp is divided into 23 pairs of chromosomes (diploid cells) and these highly regionalized sequences introduce complex patterns of regularity and irregularity to understand the gene structure, the composition of sequences of repetitive DNA and its role in the study and application of life sciences. The coding regions of the genome are estimated at ~25,000 genes which constitute 1.4% of GH. These genes are involved in a giant sea of various types of non-coding sequences which compose 98.6% of HG (misnamed popularly as “junk DNA”). The non-coding regions are characterized by many types of repeated DNA sequences, where 10.6% consists of Alu sequences, a type of SINE (short and dispersed repeated elements) sequence and preferentially located towards the genes. LINES, MIR, MER, LTR, DNA transposons and introns are another type of non-coding sequences which form about 86% of the genome. Some of these sequences overlap with each other; as with CpG islands, which complicates the analysis of genomic landscape. This standard genomic landscape was recently clarified, the last studies show that 80.4% of HG is functional due to the discovery of more than five million “switches” that operate and regulate gene activity, re-evaluating the concept of “junk DNA”. (The ENCODE Project Consortium, 2012).

Given that all these genomic variations both in worm and human produce regionalized genomic landscapes it is proposed that Fractal Geometry (FG) would allow measuring how the genetic information content is fragmented. In this paper the methodology and the nonlinear descriptive models for each of these genomes will be reviewed.

1.3 The MFA and its Application to Genome Studies

Most problems in physics are implicitly non-linear in nature, generating phenomena such as chaos theory, a science that deals with certain types of (non-linear) but very sensitive dynamic systems to initial conditions, nonetheless of deterministic rigor, that is that their behavior can be completely determined by knowing initial conditions (Peitgen et al, 1992). In turn, the FG is an appropriate tool to study the chaotic dynamic systems (CDS). In other words, the FG and chaos are closely related because the space region toward which a chaotic orbit tends asymptotically has a fractal structure (strange attractors). Therefore, the FG allows studying the framework on which CDS are defined (Moon, 1992). And this is how it is expected for the genome structure and function to be organized.

The MFA is an extension of the FG and it is related to (Shannon) information theory, disciplines that have been very useful to study the information content over a sequence of symbols. Initially, Mandelbrot established the FG in the 80’s, as a geometry capable of measuring the irregularity of nature by calculating the fractal dimension (D), an exponent derived from a power law (Mandelbrot, 1982). The value of the D gives us a measure of the level of fragmentation or the information content for a complex phenomenon. That is because the D measures the scaling degree that the fragmented self-similarity of the system has. Thus, the FG looks for self-similar properties in structures and processes at different scales of resolution and these self-similarities are organized following scaling or power laws.

Sometimes, an exponent is not sufficient to characterize a complex phenomenon; so more exponents are required. The multifractal formalism allows this, and applies when many subgroups of fractals with different scalar properties with a large number of exponents or fractal dimensions coexist simultaneously. As a result, when a spectrum of multifractal singularity measurement is generated, the scaling behavior of the frequency of symbols of a sequence can be quantified (Vélez et al, 2010).

The MFA has been implemented to study the spatial heterogeneity of theoretical and experimental fractal patterns in different disciplines. In post-genomics times, the MFA was used to study multiple biological problems (Vélez et al, 2010). Nonetheless, very little attention has been given to the use of MFA to characterize the content of the structural genetic information of the genomes obtained from the images of the Chaos Representation Game (CRG). First studies at this level were made recently to the analysis of the C. elegans genome (Vélez et al, 2010) and human genomes (Moreno et al, 2011). The MFA methodology applied for the study of these genomes will be developed below.

2. Methodology

The Multifractal Formalism from the CGR

2.1 Data Acquisition and Molecular Parameters

Databases for the C. elegans and the 36.2 Hs_ refseq HG version were downloaded from the NCBI FTP server. Then, several strategies were designed to fragment the genomic DNA sequences of different length ranges. For example, the C. elegans genome was divided into 18 fragments, Figure 2 (left) and the human genome in 9,379 fragments. According to their annotation systems, the contents of molecular parameters of coding sequences (genes, exons and introns), noncoding sequences (repetitive DNA, Alu, LINES, MIR, MER, LTR, promoters, etc.) and coding/ non-coding DNA (TTAGGC, AAAAT, AAATT, TTTTC, TTTTT, CpG islands, etc.) are counted for each sequence.

2.2 Construction of the CGR 2.3 Fractal Measurement by the Box Counting Method

Subsequently, the CGR, a recursive algorithm (Jeffrey, 1990; Restrepo et al, 2009) is applied to each selected DNA sequence, Figure 3 (above, left) and from which an image is obtained, which is quantified by the box-counting algorithm. For example, in Figure 3 (above, left) a CGR image for a human DNA sequence of 80,000 bp in length is shown. Here, dark regions represent sub-quadrants with a high number of points (or nucleotides). Clear regions, sections with a low number of points. The calculation for the D for the Koch curve by the box-counting method is illustrated by a progression of changes in the grid size, and its Cartesian graph, Table 1

The CGR image for a given DNA sequence is quantified by a standard fractal analysis. A fractal is a fragmented geometric figure whose parts are an approximated copy at full scale, that is, the figure has self-similarity. The D is basically a scaling rule that the figure obeys. Generally, a power law is given by the following expression:

Where N(E) is the number of parts required for covering the figure when a scaling factor E is applied. The power law permits to calculate the fractal dimension as:

The D obtained by the box-counting algorithm covers the figure with disjoint boxes ɛ = 1/E and counts the number of boxes required. Figure 4 (above, left) shows the multifractal measure at momentum q=1.

2.4 Multifractal Measurement

When generalizing the box-counting algorithm for the multifractal case and according to the method of moments q, we obtain the equation (3) (Gutiérrez et al, 1998; Yu et al, 2001):

Where the M_i number of points falling in the i-th grid is determined and related to the total number M₀ and ɛ to box size. Thus, the MFA is used when multiple scaling rules are applied. Figure 4 (above, right) shows the calculation of the multifractal measures at different momentum q (partition function). Here, linear regressions must have a coefficient of determination equal or close to 1. From each linear regression D are obtained, which generate an spectrum of generalized fractal dimensions D_q for all q integers, Figure 4 (below, left). So, the multifractal spectrum is obtained as the limit:

The variation of the q integer allows emphasizing different regions and discriminating their fractal a high D_q is synonymous of the structure’s richness and the properties of these regions. Negative q values emphasize the scarce regions; a high D_q indicates a lot of structure and properties in these regions. In real world applications, the limit D_qreadily approximated from the data using a linear fitting: the transformation of the equation (3) yields:

Which shows that ln In(Mi )= for set q is a linear function in the ln(ɛ), D_q can therefore be evaluated as q the slope of a fixed relationship between In(Mi )= and (q-1) ln(ɛ). The methodologies and approaches for the method of box-counting and MFA are detailed in Moreno et al, 2000, Yu et al, 2001; Moreno, 2005. For a rigorous mathematical development of MFA from images consult Multifractal system, wikipedia.

2.5 Measurement of Information Content

Subsequently, from the spectrum of generalized dimensions D_q, the degree of multifractality ΔD_q(MD) is calculated as the difference between the maximum and minimum values of D : ΔD qq = D_qmax – D_qmin (Ivanov et al, 1999). When qmaxqmin ΔD_q is high, the multifractal spectrum is rich in information and highly aperiodic, when ΔD_q is small, the resulting dimension spectrum is poor in information and highly periodic. It is expected then, that the aperiodicity in the genome would be related to highly polymorphic genomic aperiodic structures and those periodic regions with highly repetitive and not very polymorphic genomic structures. The correlation exponent t(q) = (q – 1)D_q, Figure 4 (below, right ) can also be obtained from the multifractal dimension Dq. The generalized dimension also provides significant specific information. D(q = 0) is equal to the Capacity dimension, which in this analysis is the size of the “box count”. D(q = 1) is equal to the Information dimension and D(q = 2) to the Correlation dimension. Based on these multifractal parameters, many of the structural genomic properties can be quantified, related, and interpreted.

2.6 Multifractal Parameters and Statistical and Discrimination Analyses

Once the multifractal parameters are calculated (D_q = (-20, 20), ΔDq, πq, etc.), correlations with the molecular parameters are sought. These relations are established by plotting the number of genome molecular parameters versus MD by discriminant analysis with Cartesian graphs in 2-D, Figure 5 (below, left) and 3-D and combining multifractal and molecular parameters. Finally, simple linear regression analysis, multivariate analysis, and analyses by ranges and clusterings are made to establish statistical significance.

3 Results and Discussion

3.1 Non-linear Descriptive Model for the C. elegans Genome

When analyzing the C. elegans genome with the multifractal formalism it revealed what symmetry and asymmetry on the genome nucleotide composition suggested. Thus, the multifractal scaling of the C. elegans genome is of interest because it indicates that the molecular structure of the chromosome may be organized as a system operating far from equilibrium following nonlinear laws (Ivanov et al, 1999; Burgos and Moreno-Tovar, 1996). This can be discussed from two points of view:

1) When comparing C. elegans chromosomes with each other, the X chromosome showed the lowest multifractality, Figure 5 (above). This means that the X chromosome is operating close to equilibrium, which results in an increased genetic instability. Thus, the instability of the X could selectively contribute to the molecular mechanism that determines sex (XX or X0) during meiosis. Thus, the X chromosome would be operating closer to equilibrium in order to maintain their particular sexual dimorphism.

2) When comparing different chromosome regions of the C. elegans genome, changes in multifractality were found in relation to the regional organization (at the center and arms) exhibited by the chromosomes, Figure 5 (below, left). These behaviors are associated with changes in the content of repetitive DNA, Figure 5 (below, right). The results indicated that the chromosome arms are even more complex than previously anticipated. Thus, TTAGGC telomere sequences would be operating far from equilibrium to protect the genetic information encoded by the entire chromosome.

All these biological arguments may explain why C. elegans genome is organized in a nonlinear way. These findings provide insight to quantify and understand the organization of the non-linear structure of the C. elegans genome, which may be extended to other genomes, including the HG (Vélez et al, 2010).

3.2 Nonlinear Descriptive Model for the Human Genome

Once the multifractal approach was validated in C. elegans genome, HG was analyzed exhaustively. This allowed us to propose a nonlinear model for the HG structure which will be discussed under three points of view.

1) It was found that the HG high multifractality depends strongly on the contents of Alu sequences and to a lesser extent on the content of CpG islands. These contents would be located primarily in highly aperiodic regions, thus taking the chromosome far from equilibrium and giving to it greater genetic stability, protection and attraction of mutations, Figure 6 (A-C). Thus, hundreds of regions in the HG may have high genetic stability and the most important genetic information of the HG, the genes, would be safeguarded from environmental fluctuations. Other repeated elements (LINES, MIR, MER, LTRs) showed no significant relationship,

Figure 6 (D). Consequently, the human multifractal map developed in Moreno et al, 2011 constitutes a good tool to identify those regions rich in genetic information and genomic stability. 2) The multifractal context seems to be a significant requirement for the structural and functional organization of thousands of genes and gene families. Thus, a high multifractal context (aperiodic) appears to be a “genomic attractor” for many genes (KOGs, KEEGs), Figure 6 (E) and some gene families, Figure 6 (F) are involved in genetic and deterministic processes, in order to maintain a deterministic regulation control in the genome, although most of HG sequences may be subject to a complex epigenetic control.

3) The classification of human chromosomes and chromosome regions analysis may have some medical implications (Moreno et al, 2002; Moreno et al, 2009). This means that the structure of low nonlinearity exhibited by some chromosomes (or chromosome regions) involve an environmental predisposition, as potential targets to undergo structural or numerical chromosomal alterations in Figure 6 (G). Additionally, sex chromosomes should have low multifractality to maintain sexual dimorphism and probably the X chromosome inactivation.

All these fractals and biological arguments could explain why Alu elements are shaping the HG in a nonlinearly manner (Moreno et al, 2011). Finally, the multifractal modeling of the HG serves as theoretical framework to examine new discoveries made by the ENCODE project and new approaches about human epigenomes. That is, the non-linear organization of HG might help to explain why it is expected that most of the GH is functional.

4. Conclusions

All these results show that the multifractal formalism is appropriate to quantify and evaluate genetic information contents in genomes and to relate it with the known molecular anatomy of the genome and some of the expected properties. Thus, the MFB allows interpreting in a logic manner the structural nature and variation of the genome.

The MFB allows understanding why a number of chromosomal diseases are likely to occur in the genome, thus opening a new perspective toward personalized medicine to study and interpret the GH and its diseases.

The entire genome contains nonlinear information organizing it and supposedly making it function, concluding that virtually 100% of HG is functional. Bioinformatics in general, is enriched with a novel approach (MFB) making it possible to quantify the genetic information content of any DNA sequence and their practical applications to different disciplines in biology, medicine and agriculture. This novel breakthrough in computational genomic analysis and diseases contributes to define Biology as a “hard” science.

MFB opens a door to develop a research program towards the establishment of an integrative discipline that contributes to “break” the code of human life. (http://pharmaceuticalintelligence. com/page/3/).

5. Acknowledgements

Thanks to the directives of the EISC, the Universidad del Valle and the School of Engineering for offering an academic, scientific and administrative space for conducting this research. Likewise, thanks to co authors (professors and students) who participated in the implementation of excerpts from some of the works cited here. Finally, thanks to Colciencias by the biotechnology project grant # 1103-12-16765.

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6. References

Blanco, S., & Moreno, P.A. (2007). Representación del juego del caos para el análisis de secuencias de ADN y proteínas mediante el análisis multifractal (método “box-counting”). In The Second International Seminar on Genomics and Proteomics, Bioinformatics and Systems Biology (pp. 17-25). Popayán, Colombia.         [ Links ]

Burgos, J.D., & Moreno-Tovar, P. (1996). Zipf scaling behavior in the immune system. BioSystem , 39, 227-232.         [ Links ]

C. elegans Sequencing Consortium. (1998). Genome sequence of the nematode C. elegans: a platform for investigating biology. Science , 282, 2012-2018.         [ Links ]

Gutiérrez, J.M., Iglesias A., Rodríguez, M.A., Burgos, J.D., & Moreno, P.A. (1998). Analyzing the multifractals structure of DNA nucleotide sequences. In, M. Barbie & S. Chillemi (Eds.) Chaos and Noise in Biology and Medicine (cap. 4). Hackensack (NJ): World Scientific Publishing Co.         [ Links ]

Ivanov, P.Ch., Nunes, L.A., Golberger, A.L., Havlin, S., Rosenblum, M.G., Struzikk, Z.R., & Stanley, H.E. (1999). Multifractality in human heartbeat dynamics. Nature , 399, 461-465.         [ Links ]

Jeffrey, H.J. (1990). Chaos game representation of gene structure. Nucleic Acids Research , 18, 2163-2175.         [ Links ]

Mandelbrot, B. (1982). La geometría fractal de la naturaleza. Barcelona. España: Tusquets editores.         [ Links ]

Moon, F.C. (1992). Chaotic and fractal dynamics. New York: John Wiley.         [ Links ]

Moreno, P.A. (2005). Large scale and small scale bioinformatics studies on the Caenorhabditis elegans enome. Doctoral thesis. Department of Biology and Biochemistry, University of Houston, Houston, USA.         [ Links ]

Moreno, P.A., Burgos, J.D., Vélez, P.E., Gutiérrez, J.M., & et al., (2000). Multifractal analysis of complete genomes. In P roceedings of the 12th International Genome Sequencing and Analysis Conference (pp. 80-81). Miami Beach (FL).         [ Links ]

Moreno, P.A., Rodríguez, J.G., Vélez, P.E., Cubillos, J.R., & Del Portillo, P. (2002). La genómica aplicada en salud humana. Colombia Ciencia y Tecnología. Colciencias , 20, 14-21.         [ Links ]

Moreno, P.A., Vélez, P.E., & Burgos, J.D. (2009). Biología molecular, genómica y post-genómica. Pioneros, principios y tecnologías. Popayán, Colombia: Editorial Universidad del Cauca.         [ Links ]

Moreno, P.A., Vélez, P.E., Martínez, E., Garreta, L., Díaz, D., Amador, S., Gutiérrez, J.M., et. al. (2011). The human genome: a multifractal analysis. BMC Genomics , 12, 506.         [ Links ]

Mount, D.W. (2004). Bioinformatics. Sequence and ge nome analysis. New York: Cold Spring Harbor Laboratory Press.         [ Links ]

Peitgen, H.O., Jürgen, H., & Saupe D. (1992). Chaos and Fractals. New Frontiers of Science. New York: Springer-Verlag.         [ Links ]

Restrepo, S., Pinzón, A., Rodríguez, L.M., Sierra, R., Grajales, A., Bernal, A., Barreto, E. et. al. (2009). Computational biology in Colombia. PLoS Computational Biology, 5 (10), e1000535.         [ Links ]

The ENCODE Project Consortium. (2012). An integrated encyclopedia of DNA elements in the human genome. Nature , 489, 57-74.         [ Links ]

Vélez, P.E., Garreta, L.E., Martínez, E., Díaz, N., Amador, S., Gutiérrez, J.M., Tischer, I., & Moreno, P.A. (2010). The Caenorhabditis elegans genome: a multifractal analysis. Genet and Mol Res , 9, 949-965.         [ Links ]

Venter, J.C., Adams, M.D., Myers, E.W., Li, P.W., & et al. (2001). The sequence of the human genome. Science , 291, 1304-1351.         [ Links ]

Yu, Z.G., Anh, V., & Lau, K.S. (2001). Measure representation and multifractal analysis of complete genomes. Physical Review E: Statistical, Nonlinear, and Soft Matter Physics , 64, 031903.         [ Links ]

 

Other articles on Bioinformatics on this Open Access Journal include:

Bioinformatics Tool Review: Genome Variant Analysis Tools

2017 Agenda – BioInformatics: Track 6: BioIT World Conference & Expo ’17, May 23-35, 2017, Seaport World Trade Center, Boston, MA

Better bioinformatics

Broad Institute, Google Genomics combine bioinformatics and computing expertise

Autophagy-Modulating Proteins and Small Molecules Candidate Targets for Cancer Therapy: Commentary of Bioinformatics Approaches

CRACKING THE CODE OF HUMAN LIFE: The Birth of BioInformatics & Computational Genomics

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June 4, 2018 – Department of Defense Medical Innovation and Biodefense Forum, BIO 2018! at Boston Convention & Exhibition Center

Posted in Bio Instrumentation in Experimental Life Sciences Research, Bioengineering & reverse engineering design, Biological Engineering, Biomarkers & Medical Diagnostics, Biomedical Measurement Science, BioTechnology - Venture Creation, Conference Coverage with Social Media on June 4, 2018| Leave a Comment »

June 4, 2018 – Department of Defense Medical Innovation and Biodefense Forum, BIO 2018! at Boston Convention & Exhibition Center

Announcement

Aviva Lev-Ari, PhD, RN,

https://mybio.org/profile/member/2029564?profile_tabs=profile

Founder and Director of LPBI Group will be in attendance covering the event in REAL TIME

https://pharmaceuticalintelligence.com/2018/05/26/bio-2018-june-4-7-2018-at-boston-convention-exhibition-center/

@pharma_BI

@AVIVA1950

for

#BIO2018

#MakingBIOHistory

@BIOConvention

9:00 AM–12:00 PM Jun 4, 2018

Department of Defense Medical Innovation and Biodefense Forum

Speakers

Moderator, Panel 1: Phyllis Arthur Vice President, Infectious Diseases & Diagnostics Policy atBiotechnology Innovation Organization (BIO)

• How DoD can assist Industry to commercialize technologies
• How the coordination in the Infectious disease takes place

Panel 2: Timothy Belski Joint Product Lead for the Advanced Development & Manufacturing Capability at Joint Program Executive Office for Chemical and Biological Defense, Medical Countermeasure Systems

• Manufacturing for DoD
• Infrastructure to manage across Government RFP Process

Panel 3: Lt. Matthew Clark Joint Product Manager, Chemical Defense Pharmaceuticals at Medical Countermeasure Systems

• Devices requires detailed engineering for use in Field hospitals
• Regulatory, Scheduling and Engineering problems
• Development is for all the Forces of the US and for all the Forces of US Allies — design for CIvilian first respnders as well
• Some partners are commercial Partners, they need to approach DoD with novel product concept
• FDA approved vs Right to Try – DoD uses both

Panel 1: Captain  Joseph Cohn Chief, Research Program Administration Division J9, Research & Development Directorate at Defense Health Agency (DHA)

• Small business Program, success in bringing product to market
• 20 years ago: Communities of interest – 20 orgs community common goals in Health Care, rehabilitation after coming home,
• MROC – Conference in Florida DoD to explain the Public the process of engagement with Do

Panel 1: Dr. Mark Dertzbaugh Civilian Deputy to the Principal Assistant for Research & Technology at U.S. Army Medical Research and Materiel Command

Moderator , Panel 3: Hannah Feldman Public Affairs Specialist atJoint Program Executive Office for Chemical and Biological Defense, Medical Countermeasure Systems

• Interagency partnership

Moderator, Panel 2: Tom Handel General Manager and President at Meridian Medical Technologies, Inc.

Panel 1 & 2 & 3: Dr. David Hone Chief Scientist, Vaccine and Therapeutic Division, Joint Science and Technology Office atDefense Threat Reduction Agency

• DoD starts with good ideas, concept studies – innovators
• Collaborations with Academia, we are available to be approached
• DoD will partner with small businesses to avoid the Regulatory process  – to save time and resources in the commercialization process
• How a civilian concept FITS the needs of DoD
• Sustaining an innovation along the years
• Need for small business to approach DoD to make the contact
• Where is a small business in the Development cycle? DoD can help calibrate
• A System of Systems: Diagnostics drive decisions
• develop partnerships in consortia
• Six month to vaccinate 17,000 with a Vaccine for EBOLA
• DoD of respective countries are collaborating with US DoD

Panel 3: Nicole Kilgore Joint Product Lead for the Platforms for Rapid Integrated Solutions for Medical Countermeasures atJoint Program Executive Office for Chemical and Biological Defense, Medical Countermeasure Systems

• Threat environment changes over time vs modify known threats
• Monoclonal antibody – the Industry developed the manufacturing technology and DoD is user of Industry products

Panel 1: Lt. Col. Cindy Landgren, PhD Deputy, Medical Programs at Office of Deputy Assistant Secretary of Defense, Chemical and Biological Defense

• All research for the Joint Force, Chemical, Biological,
• Short time to market solutions are of interest for DoD to identify
• Military relevance: Key for funding
• Announcements of DoD on WHAT PROBLEMS DoD tries to solve
• DoD and HHS — aligned for common solution to avoid redundancy
• Development of profilaxix is very expensive, DoD budget has competing goals: Next soldier suit,

Panel 2: Carmen Maher Director, Medical Regulatory Affairs atJoint Program Executive Office for Chemical and Biological Defense

Panel 2: Col. Nelson Michael Deputy Commander at Walter Reed Army Institute of Research

• FDA and DoD need to collaborate for DoDs needs

Panel 2: Dr. James Phillips Projects Officer, Office of the Principal Assistant for Acquisitions at U.S. Army Medical Research and Materiel Command

• Order transaction authority,
• Congress set aside a budget for small businesses to use accounting systems for Small business to interact with DoD
• How to get a digital signal to the brain: Expertise in many disciplines: EE, Ethomology

Panel 1: Dr. Jason Roos, PhD Deputy Program Executive Officer at Joint Program Executive Office for Chemical and Biological Defense

• Delivery, test , evaluation, develop sensors, IS to manage threats, Diagnostics,
• How to do Business with Industry?
• Congress asked for a Consorsium to engage with Industry in a different form than we engaged before
• Partnerships for out of the box thinking and going quickly – the appetite for is greater then evr before
• Successful area: Diagnostics – adoptation of existing diagnostics for military applications
• Platform technologies: Metabolic, Vaccines,
• Leverage existing technologies to solve DoD concerns

Panel 2: Dr. Mike Stebbins Consortium Manager at Advanced Technology International

• involved with MCS help Government to learn how to build their Office

Panel 3: Col. Gary Wheeler, Commander, U.S. Army Medical Research Institute of Infectious Diseases at U.S. Army Medical Research and Materiel Command

• Genomic, Proteomics, therapeutics candidates, Prophylaxis as Vaccines
• In the event of an outbreak: clinicians, 1st responders

Panel 2: Clay Holloway, Director of Strategic Initiatives, Joint Project Manager, Medical Countermeasure Systems (JPM-MCS)

• Partnering is key
• capability requirements: broad spectrum capabilities
• Decision tools to be used at studies for data analysis for decision making
• Risks in partnership: DoD needs to evaluate ideas for next generation to SKIP one generation
• How to used different agreement strategically? Streamline DoD Methods
• Have continuous access to assets

 

LOCATION

Room 205ABC, Level 2

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Conduction, graphene, elements and light

Posted in Alzheimer's Disease, Bioengineering & reverse engineering design, Curation, Developmental biology, Hematopoiesis, Human Immune System in Health and in Disease, Immunotherapy, Innovations, Lasers and photonics, Materials Science & Engineering, Medical Imaging Technology, Microbiology, Nanotechnology for Drug Delivery, Neurodegenerative Diseases, tagged biomedical, Electronics, embryonic stem cells, light, MRI, Nanotech/Materials Science, Surface plasmon resonance on March 27, 2016| Leave a Comment »

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.

references:

• Antonis N. Andriotis, Ernst Richter, and Madhu Menon. Prediction of a new graphenelike Si2BN solid. Phys. Rev. B 93, 081413(R) – Published 26 February 2016; DOI: 10.1103/PhysRevB.93.081413

 

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 products, and 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.

references:

• Samuel R. Anderson, Mahsa Mohammadtaheri, Dipesh Kumar, Anthony P. O’Mullane, Matthew R. Field, Rajesh Ramanathan, Vipul Bansal. Robust Nanostructured Silver and Copper Fabrics with Localized Surface Plasmon Resonance Property for Effective Visible Light Induced Reductive Catalysis. Advanced Materials Interfaces, 2016; DOI: 10.1002/admi.201500632

 

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:

• Thomas Theis, Gerardo X. Ortiz Jr., Angus W. J. Logan, Kevin E. Claytor, Yesu Feng, William P. Huhn, Volker Blum, Steven J. Malcolmson, Eduard Y. Chekmenev, Qiu Wang and Warren S. Warren. Direct and cost-efficient hyperpolarization of long-lived nuclear spin states on universal ¹⁵N₂-diazirine molecular tags. Science Advances, March 25, 2016. DOI: 10.1126/sciadv.1501438

[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

 

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

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