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Hybrid lipid bioelectronic membranes

Larry H. Bernstein, MD, FCAP, Curator

LPBI

 

Hybrid solid-state chips and biological cells integrated at molecular level

Biological ion channels combine with solid-state transistors to create a new kind of hybrid bioelectronics. Imagine chips with dog-like capability to taste and smell, or even recognize specific molecules.
http://www.kurzweilai.net/hybrid-solid-state-chips-and-biological-cells-integrated-at-molecular-level
Illustration depicting a biocell attached to a CMOS integrated circuit with a membrane containing sodium-potassium pumps in pores. Energy is stored chemically in ATP molecules. When the energy is released as charged ions (which are then converted to electrons to power the chip at the bottom of the experimental device), the ATP is converted to ADP + inorganic phosphate. (credit: Trevor Finney and Jared Roseman/Columbia Engineering)

Columbia Engineering researchers have combined biological and solid-state components for the first time, opening the door to creating entirely new artificial biosystems.

In this experiment, they used a biological cell to power a conventional solid-state complementary metal-oxide-semiconductor (CMOS) integrated circuit. An artificial lipid bilayer membrane containing adenosine triphosphate (ATP)-powered ion pumps (which provide energy for cells) was used as a source of ions (which were converted to electrons to power the chip).

The study, led by Ken Shepard, Lau Family Professor of Electrical Engineering and professor of biomedical engineering at Columbia Engineering, was published online today (Dec. 7, 2015) in an open-access paper in Nature Communications.

How to build a hybrid biochip

Living systems achieve this functionality with their own version of electronics based on lipid membranes and ion channels and pumps, which act as a kind of “biological transistor.” Charge in the form of ions carry energy and information, and ion channels control the flow of ions across cell membranes.

Solid-state systems, such as those in computers and communication devices, use electrons; their electronic signaling and power are controlled by field-effect transistors.

To build a prototype of their hybrid system, Shepard’s team packaged a CMOS integrated circuit (IC) with an ATP-harvesting “biocell.” In the presence of ATP, the system pumped ions across the membrane, producing an electrical potential (voltage)* that was harvested by the integrated circuit.

“We made a macroscale version of this system, at the scale of several millimeters, to see if it worked,” Shepard notes. “Our results provide new insight into a generalized circuit model, enabling us to determine the conditions to maximize the efficiency of harnessing chemical energy through the action of these ion pumps. We will now be looking at how to scale the system down.”

While other groups have harvested energy from living systems, Shepard and his team are exploring how to do this at the molecular level, isolating just the desired function and interfacing this with electronics. “We don’t need the whole cell,” he explains. “We just grab the component of the cell that’s doing what we want. For this project, we isolated the ATPases because they were the proteins that allowed us to extract energy from ATP.”

The capability of a bomb-sniffing dog, no Alpo required

Next, the researchers plan to go much further, such as recognizing specific molecules and giving chips the potential to taste and smell.

The ability to build a system that combines the power of solid-state electronics with the capabilities of biological components has great promise, they believe. “You need a bomb-sniffing dog now, but if you can take just the part of the dog that is useful — the molecules that are doing the sensing — we wouldn’t need the whole animal,” says Shepard.

The technology could also provide a power source for implanted electronic devices in ATP-rich environments such as inside living cells, the researchers suggest.

*  “In general, integrated circuits, even when operated at the point of minimum energy in subthreshold, consume on the order of 10−2 W mm−2 (or assuming a typical silicon chip thickness of 250 μm, 4 × 10−2 W mm−3). Typical cells, in contrast, consume on the order of 4 × 10−6 W mm−3. In the experiment, a typical active power dissipation for the IC circuit was 92.3 nW, and the active average harvesting power was 71.4 fW for the biocell (the discrepancy is managed through duty-cycled operation of the IC).” — Jared M. Roseman et al./Nature Communications

 

Hybrid integrated biological–solid-state system powered with adenosine triphosphate

Jared M. RosemanJianxun LinSiddharth RamakrishnanJacob K. Rosenstein & Kenneth L. Shepard
Nature Communications 7 Dec 2015; 6(10070)
     http://dx.doi.org:/10.1038/ncomms10070

There is enormous potential in combining the capabilities of the biological and the solid state to create hybrid engineered systems. While there have been recent efforts to harness power from naturally occurring potentials in living systems in plants and animals to power complementary metal-oxide-semiconductor integrated circuits, here we report the first successful effort to isolate the energetics of an electrogenic ion pump in an engineered in vitro environment to power such an artificial system. An integrated circuit is powered by adenosine triphosphate through the action of Na+/K+ adenosine triphosphatases in an integrated in vitro lipid bilayer membrane. The ion pumps (active in the membrane at numbers exceeding 2 × 106mm−2) are able to sustain a short-circuit current of 32.6pAmm−2 and an open-circuit voltage of 78mV, providing for a maximum power transfer of 1.27pWmm−2 from a single bilayer. Two series-stacked bilayers provide a voltage sufficient to operate an integrated circuit with a conversion efficiency of chemical to electrical energy of 14.9%.

 

Figure 1: Fully hybrid biological–solid-state system.

 

 

Fully hybrid biological-solid-state system.

http://www.nature.com/ncomms/2015/151207/ncomms10070/images/ncomms10070-f1.jpg

(a) Illustration depicting biocell attached to CMOS integrated circuit. (b) Illustration of membrane in pore containing sodium–potassium pumps. (c) Circuit model of equivalent stacked membranes, =2.1pA, =98.6G, =575G and =75pF, Ag/AgCl electrode equivalent resistance RWE+RCE<20k, energy-harvesting capacitor CSTOR=100nF combined with switch as an impedance transformation network (only one switch necessary due to small duty cycle), and CMOS IC voltage doubler and resistor representing digital switching load. RL represents the four independent ring oscillator loads. (d) Equivalent circuit detail of stacked biocell. (e) Switched-capacitor voltage doubler circuit schematic.

 

The energetics of living systems are based on electrochemical membrane potentials that are present in cell plasma membranes, the inner membrane of mitochondria, or the thylakoid membrane of chloroplasts1. In the latter two cases, the specific membrane potential is known as the proton-motive force and is used by proton adenosine triphosphate (ATP) synthases to produce ATP. In the former case, Na+/K+-ATPases hydrolyse ATP to maintain the resting potential in most cells.

While there have been recent efforts to harness power from some naturally occurring potentials in living systems that are the result of ion pump action both in plants2 and animals3, 4 to power complementary metal-oxide semiconductor (CMOS) integrated circuits (ICs), this work is the first successful effort to isolate the energetics of an electrogenic ion pump in an engineered in vitroenvironment to power such an artificial system. Prior efforts to harness power from in vitromembrane systems incorporating ion-pumping ATPases5, 6, 7, 8, 9 and light-activated bacteriorhodopsin9, 10, 11 have been limited by difficulty in incorporating these proteins in sufficient quantity to attain measurable current and in achieving sufficiently large membrane resistances to harness these currents. Both problems are solved in this effort to power an IC from ATP in an in vitro environment. The resulting measurements provide new insight into a generalized circuit model, which allows us to determine the conditions to maximize the efficiency of harnessing chemical energy through the action of electrogenic ion pumps.

 

ATP-powered IC

Figure 1a shows the complete hybrid integrated system, consisting of a CMOS IC packaged with an ATP-harvesting ‘biocell’. The biocell consists of two series-stacked ATPase bearing suspended lipid bilayers with a fluid chamber directly on top of the IC. Series stacking of two membranes is necessary to provide the required start-up voltage for IC and eliminates the need for an external energy source, which is typically required to start circuits from low-voltage supplies2, 3. As shown inFig. 1c, a matching network in the form of a switched capacitor allows the load resistance of the IC to be matched to that presented by the biocell. In principle, the switch S can be implicit. The biocell charges CSTOR until the self start-up voltage, Vstart, is reached. The chip then operates until the biocell voltage drops below the minimum supply voltage for operation, Vmin. Active current draw from the IC stops at this point, allowing the charge to build up again on CSTOR. In our case, however, the IC leakage current exceeds 13.5nA at Vstart, more than can be provided by the biocell. As a result, an explicit transistor switch and comparator (outside of the IC) are used for this function in the experimental results presented here, which are not powered by the biocell and not included in energy efficiency calculations (see Supplementary Discussion for additional details). The energy from the biocell is used to operate a voltage converter (voltage doubler) and some simple inverter-based ring oscillators in the IC, which receive power from no other sources.

Figure 1: Fully hybrid biological–solid-state system.

http://www.nature.com/ncomms/2015/151207/ncomms10070/images/ncomms10070-f1.jpg

 

……..   Prior to the addition of ATP, the membrane produces no electrical power and has an Rm of 280G. A 1.7-pA short-circuit (SC) current (Fig. 2b) through the membrane is observed upon the addition of ATP (final concentration 3mM) to the cis chamber where functional, properly oriented enzymes generate a net electrogenic pump current. To perform these measurements, currents through each membrane of the biocell are measured using a voltage-clamp amplifier (inset of Fig. 2b) with a gain of 500G with special efforts taken to compensate amplifier leakage currents. Each ATPase transports three Na+ ions from the cis chamber to the trans chamber and two K+ ions from thetrans chamber to the cis chamber (a net charge movement of one cation) for every molecule of ATP hydrolysed. At a rate of 100 hydrolysis events per second under zero electrical (SC) bias13, this results in an electrogenic current of ~16aA. The observed SC current corresponds to about 105 active ATPases in the membrane or a concentration of about 2 × 106mm−2, about 5% of the density of channels occurring naturally in mammalian nerve fibres14. It is expected that half of the channels inserted are inactive because they are oriented incorrectly.

Figure 2: Single-cell biocell characterization.

http://www.nature.com/ncomms/2015/151207/ncomms10070/images_article/ncomms10070-f2.jpg

(a)…Pre-ATP data linear fit (black line) slope yield Rm=280G. Post ATP data fit to a Boltzmann curve, slope=0.02V (blue line). Post-ATP linear fit (red line) yields Ip=−1.8pA and Rp=61.6G, which corresponds to a per-ATP source resistance of 6.16 × 1015. The current due to membrane leakage through R_{m} is subtracted in the post-ATP curve…. (b)…

 

Current–voltage characteristics of the ATPases

Figure 2a shows the complete measured current–voltage (IV) characteristic of a single ATPase-bearing membrane in the presence of ATP. The current due to membrane leakage through Rm is subtracted in the post-ATP curve. The IV characteristic fits a Boltzmann sigmoid curve, consistent with sodium–potassium pump currents measured on membrane patches at similar buffer conditions13, 15, 16. This nonlinear behaviour reflects the fact that the full ATPase transport cycle (three Na+ ions from cis to trans and two K+ ions from trans to cis) time increases (the turn-over rate, kATP, decreases) as the membrane potential increases16. No effect on pump current is expected from any ion concentration gradients produced by the action of the ATPases (seeSupplementary Discussion). Using this Boltzmann fit, we can model the biocell as a nonlinear voltage-controlled current source IATPase (inset Fig. 2a), in which the current produced by this source varies as a function of Vm. In the fourth quadrant, where the cell is producing electrical power, this model can be linearized as a Norton equivalent circuit, consisting of a DC current source (Ip) in parallel with a current-limiting resistor (Rp), which acts to limit the current delivered to the load at increasing bias (IATPase~IpVm/Rp). Figure 2c shows the measured and simulated charging of Cm for a single membrane (open-circuited voltage). A custom amplifier with input resistance Rin>10T was required for this measurement (see Electrical Measurement Methods).

 

Reconciling operating voltage differences

The electrical characteristics of biological systems and solid-state systems are mismatched in their operating voltages. The minimum operating voltage of solid-state systems is determined by the need for transistors to modulate a Maxwell–Boltzmann (MB) distribution of carriers by several orders of magnitude through the application of a potential that is several multiples of kT/q (where kis Boltzmann’s constant, T is the temperature in degrees Kelvin and q is the elementary charge). Biological systems, while operating under the same MB statistics, have no such constraints for operating ion channels since they are controlled by mechanical (or other conformational) processes rather than through modulation of a potential barrier. To bridge this operating voltage mismatch, the circuit includes a switched-capacitor voltage doubler (Fig. 1d) that is capable of self-startup from voltages as low Vstart=145mV (~5.5kT/q) and can be operated continuously from input voltages from as low as Vmin=110mV (see Supplementary Discussion)…..

 

Maximizing the efficiency of harvesting energy from ATP

Solid-state systems and biological systems are also mismatched in their operating impedances. In our case, the biocell presents a source impedance, =84.2G, while the load impedance presented by the complete integrated circuit (including both the voltage converter and ring oscillator loads) is approximately RIC=200k. (The load impedance, RL, of the ring oscillators alone is 305k.) This mismatch in source and load impedance is manifest in large differences in power densities. In general, integrated circuits, even when operated at the point of minimum energy in subthreshold, consume on the order of 10−2Wmm−2 (or assuming a typical silicon chip thickness of 250μm, 4 × 10−2Wmm−3) (ref. 17). Typical cells, in contrast, consume on the order of 4 × 10−6Wmm−3 (ref. 18). In our case, a typical active power dissipation for our circuit is 92.3nW, and the active average harvesting power is 71.4fW for the biocell. This discrepancy is managed through duty-cycled operation of the IC in which the circuit is largely disabled for long periods of time (Tcharge), integrating up the power onto a storage capacitor (CSTOR), which is then expended in a very brief period of activity (Trun), as shown in Fig. 3a.

The overall efficiency of the system in converting chemical energy to the energy consumed in the load ring oscillator (η) is given by the product of the conversion efficiency of the voltage doubler (ηconverter) and the conversion efficiency of chemical energy to electrical energy in the biocell (ηbiocell), η=ηconverter × ηbiocell. ηconverter is relatively constant over the range of input voltages at ~59%, as determined by various loading test circuits included in the chip design (Supplementary Figs 1–6). ηbiocell, however, varies with transmembrane potential Vm. η is the efficiency in transferring power to the power ring oscillator loads from the ATP harvested by biocell.

…….

To first order, the energy made available to the Na+/K+-ATPase by the hydrolysis of ATP is independent of the chemical or electric potential of the membrane and is given by |ΔGATP|/(qNA), where ΔGATP is the Gibbs free energy change due to the ATP hydrolysis reaction per mole of ATP at given buffer conditions and NA is Avogadro’s number. Since every charge that passes through IATPase corresponds to a single hydrolysis event, we can use two voltage sources in series with IATPase to independently account for the energy expended by the pumps both in moving charge across the electric potential difference and in moving ions across the chemical potential difference. The dependent voltage source Vloss in this branch fixes the voltage across IATPase, and the total power produced by the pump current source is (|ΔGATP|/NA)(NkATP), which is the product of the energy released per molecule of ATP, the number of active ATPases and the ATP turnover rate. The power dissipated in voltage source Vchem models the work performed by the ATPases in transporting ions against a concentration gradient. In the case of the Na+/K+ ATPase,Vchem is given by . The power dissipated in this source is introduced back into the circuit in the power generated by the Nernst independent voltage sources, and . The power dissipated in the dependent voltage source Vloss models any additional power not used to perform chemical or electrical work. ……

 

Integration of ATP-harvesting ion pumps could provide a means to power future CMOS microsystems scaled to the level of individual cells22. In molecular diagnostics, the integration of pore-forming proteins such as alpha haemolysin23 or MspA porin24 with CMOS electronics is already finding application in DNA sequencing25. Exploiting the large diversity of function available in transmembrane proteins in these hybrid systems could, for example, lead to highly specific sensing platforms for airborne odorants or soluble molecular entities26, 27. Heavily multiplexed platforms could become high-throughput in vitro drug-screening platforms against this diversity of function. In addition, integration of transmembrane proteins with CMOS may become a convenient alternative to fluorescence for coupling to synthetic biological systems28.

 

Roseman, J. M. et al. Hybrid integrated biological–solid-state system powered with adenosine triphosphate. Nat. Commun. 6:10070      http://dx.doi.org:/10.1038/ncomms10070 (2015).

 

 

  • Rottenberg, H. The measurement of membrane potential and deltapH in cells, organelles, and vesicles. Methods Enzymol. 55, 547569 (1979).
  • Himes, C., Carlson, E., Ricchiuti, R. J., Otis, B. P. & Parviz, B. A. Ultralow voltage nanoelectronics powered directly, and solely, from a tree. IEEE Trans. Nanotechnol. 9, 25(2010).
  • Mercier, P. P., Lysaght, A. C., Bandyopadhyay, S., Chandrakasan, A. P. & Stankovic, K. M.Energy extraction from the biologic battery in the inner ear. Nat. Biotechnol. 30, 12401243(2012).
  • Halámková, L. et al. Implanted Biofuel Cell Operating in a Living Snail. J. Am. Chem. Soc.134, 50405043 (2012).

 

 

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Summary of Translational Medicine – e-Series A: Cardiovascular Diseases, Volume Four – Part 1


Summary of Translational Medicine – e-Series A: Cardiovascular Diseases, Volume Four – Part 1

Author and Curator: Larry H Bernstein, MD, FCAP

and

Curator: Aviva Lev-Ari, PhD, RN

 

Part 1 of Volume 4 in the e-series A: Cardiovascular Diseases and Translational Medicine, provides a foundation for grasping a rapidly developing surging scientific endeavor that is transcending laboratory hypothesis testing and providing guidelines to:

  • Target genomes and multiple nucleotide sequences involved in either coding or in regulation that might have an impact on complex diseases, not necessarily genetic in nature.
  • Target signaling pathways that are demonstrably maladjusted, activated or suppressed in many common and complex diseases, or in their progression.
  • Enable a reduction in failure due to toxicities in the later stages of clinical drug trials as a result of this science-based understanding.
  • Enable a reduction in complications from the improvement of machanical devices that have already had an impact on the practice of interventional procedures in cardiology, cardiac surgery, and radiological imaging, as well as improving laboratory diagnostics at the molecular level.
  • Enable the discovery of new drugs in the continuing emergence of drug resistance.
  • Enable the construction of critical pathways and better guidelines for patient management based on population outcomes data, that will be critically dependent on computational methods and large data-bases.

What has been presented can be essentially viewed in the following Table:

 

Summary Table for TM - Part 1

Summary Table for TM – Part 1

 

 

 

There are some developments that deserve additional development:

1. The importance of mitochondrial function in the activity state of the mitochondria in cellular work (combustion) is understood, and impairments of function are identified in diseases of muscle, cardiac contraction, nerve conduction, ion transport, water balance, and the cytoskeleton – beyond the disordered metabolism in cancer.  A more detailed explanation of the energetics that was elucidated based on the electron transport chain might also be in order.

2. The processes that are enabling a more full application of technology to a host of problems in the environment we live in and in disease modification is growing rapidly, and will change the face of medicine and its allied health sciences.

 

Electron Transport and Bioenergetics

Deferred for metabolomics topic

Synthetic Biology

Introduction to Synthetic Biology and Metabolic Engineering

Kristala L. J. Prather: Part-1    <iBiology > iBioSeminars > Biophysics & Chemical Biology >

http://www.ibiology.org Lecturers generously donate their time to prepare these lectures. The project is funded by NSF and NIGMS, and is supported by the ASCB and HHMI.
Dr. Prather explains that synthetic biology involves applying engineering principles to biological systems to build “biological machines”.

Dr. Prather has received numerous awards both for her innovative research and for excellence in teaching.  Learn more about how Kris became a scientist at
Prather 1: Synthetic Biology and Metabolic Engineering  2/6/14IntroductionLecture Overview In the first part of her lecture, Dr. Prather explains that synthetic biology involves applying engineering principles to biological systems to build “biological machines”. The key material in building these machines is synthetic DNA. Synthetic DNA can be added in different combinations to biological hosts, such as bacteria, turning them into chemical factories that can produce small molecules of choice. In Part 2, Prather describes how her lab used design principles to engineer E. coli that produce glucaric acid from glucose. Glucaric acid is not naturally produced in bacteria, so Prather and her colleagues “bioprospected” enzymes from other organisms and expressed them in E. coli to build the needed enzymatic pathway. Prather walks us through the many steps of optimizing the timing, localization and levels of enzyme expression to produce the greatest yield. Speaker Bio: Kristala Jones Prather received her S.B. degree from the Massachusetts Institute of Technology and her PhD at the University of California, Berkeley both in chemical engineering. Upon graduation, Prather joined the Merck Research Labs for 4 years before returning to academia. Prather is now an Associate Professor of Chemical Engineering at MIT and an investigator with the multi-university Synthetic Biology Engineering Reseach Center (SynBERC). Her lab designs and constructs novel synthetic pathways in microorganisms converting them into tiny factories for the production of small molecules. Dr. Prather has received numerous awards both for her innovative research and for excellence in teaching.

VIEW VIDEOS

https://www.youtube.com/watch?feature=player_embedded&v=ndThuqVumAk#t=0

https://www.youtube.com/watch?feature=player_embedded&v=ndThuqVumAk#t=12

https://www.youtube.com/watch?feature=player_embedded&v=ndThuqVumAk#t=74

https://www.youtube.com/watch?feature=player_embedded&v=ndThuqVumAk#t=129

https://www.youtube.com/watch?feature=player_embedded&v=ndThuqVumAk#t=168

https://www.youtube.com/watch?feature=player_embedded&v=ndThuqVumAk

 

II. Regulatory Effects of Mammalian microRNAs

Calcium Cycling in Synthetic and Contractile Phasic or Tonic Vascular Smooth Muscle Cells

in INTECH
Current Basic and Pathological Approaches to
the Function of Muscle Cells and Tissues – From Molecules to HumansLarissa Lipskaia, Isabelle Limon, Regis Bobe and Roger Hajjar
Additional information is available at the end of the chapter
http://dx.doi.org/10.5772/48240
1. Introduction
Calcium ions (Ca ) are present in low concentrations in the cytosol (~100 nM) and in high concentrations (in mM range) in both the extracellular medium and intracellular stores (mainly sarco/endo/plasmic reticulum, SR). This differential allows the calcium ion messenger that carries information
as diverse as contraction, metabolism, apoptosis, proliferation and/or hypertrophic growth. The mechanisms responsible for generating a Ca signal greatly differ from one cell type to another.
In the different types of vascular smooth muscle cells (VSMC), enormous variations do exist with regard to the mechanisms responsible for generating Ca signal. In each VSMC phenotype (synthetic/proliferating and contractile [1], tonic or phasic), the Ca signaling system is adapted to its particular function and is due to the specific patterns of expression and regulation of Ca.
For instance, in contractile VSMCs, the initiation of contractile events is driven by mem- brane depolarization; and the principal entry-point for extracellular Ca is the voltage-operated L-type calcium channel (LTCC). In contrast, in synthetic/proliferating VSMCs, the principal way-in for extracellular Ca is the store-operated calcium (SOC) channel.
Whatever the cell type, the calcium signal consists of  limited elevations of cytosolic free calcium ions in time and space. The calcium pump, sarco/endoplasmic reticulum Ca ATPase (SERCA), has a critical role in determining the frequency of SR Ca release by upload into the sarcoplasmic
sensitivity of  SR calcium channels, Ryanodin Receptor, RyR and Inositol tri-Phosphate Receptor, IP3R.
Synthetic VSMCs have a fibroblast appearance, proliferate readily, and synthesize increased levels of various extracellular matrix components, particularly fibronectin, collagen types I and III, and tropoelastin [1].
Contractile VSMCs have a muscle-like or spindle-shaped appearance and well-developed contractile apparatus resulting from the expression and intracellular accumulation of thick and thin muscle filaments [1].
Schematic representation of Calcium Cycling in Contractile and Proliferating VSMCs

Schematic representation of Calcium Cycling in Contractile and Proliferating VSMCs

 

Figure 1. Schematic representation of Calcium Cycling in Contractile and Proliferating VSMCs.

Left panel: schematic representation of calcium cycling in quiescent /contractile VSMCs. Contractile re-sponse is initiated by extracellular Ca influx due to activation of Receptor Operated Ca (through phosphoinositol-coupled receptor) or to activation of L-Type Calcium channels (through an increase in luminal pressure). Small increase of cytosolic due IP3 binding to IP3R (puff) or RyR activation by LTCC or ROC-dependent Ca influx leads to large SR Ca IP3R or RyR clusters (“Ca -induced Ca SR calcium pumps (both SERCA2a and SERCA2b are expressed in quiescent VSMCs), maintaining high concentration of cytosolic Ca and setting the sensitivity of RyR or IP3R for the next spike.
Contraction of VSMCs occurs during oscillatory Ca transient.
Middle panel: schematic representa tion of atherosclerotic vessel wall. Contractile VSMC are located in the media layer, synthetic VSMC are located in sub-endothelial intima.
Right panel: schematic representation of calcium cycling in quiescent /contractile VSMCs. Agonist binding to phosphoinositol-coupled receptor leads to the activation of IP3R resulting in large increase in cytosolic Ca calcium pumps (only SERCA2b, having low turnover and low affinity to Ca depletion leads to translocation of SR Ca sensor STIM1 towards PM, resulting in extracellular Ca influx though opening of Store Operated Channel (CRAC). Resulted steady state Ca transient is critical for activation of proliferation-related transcription factors ‘NFAT).
Abbreviations: PLC – phospholipase C; PM – plasma membrane; PP2B – Ca /calmodulin-activated protein phosphatase 2B (calcineurin); ROC- receptor activated channel; IP3 – inositol-1,4,5-trisphosphate, IP3R – inositol-1,4,5- trisphosphate receptor; RyR – ryanodine receptor; NFAT – nuclear factor of activated T-lymphocytes; VSMC – vascular smooth muscle cells; SERCA – sarco(endo)plasmic reticulum Ca sarcoplasmic reticulum.

 

Time for New DNA Synthesis and Sequencing Cost Curves

By Rob Carlson

I’ll start with the productivity plot, as this one isn’t new. For a discussion of the substantial performance increase in sequencing compared to Moore’s Law, as well as the difficulty of finding this data, please see this post. If nothing else, keep two features of the plot in mind: 1) the consistency of the pace of Moore’s Law and 2) the inconsistency and pace of sequencing productivity. Illumina appears to be the primary driver, and beneficiary, of improvements in productivity at the moment, especially if you are looking at share prices. It looks like the recently announced NextSeq and Hiseq instruments will provide substantially higher productivities (hand waving, I would say the next datum will come in another order of magnitude higher), but I think I need a bit more data before officially putting another point on the plot.

 

cost-of-oligo-and-gene-synthesis

cost-of-oligo-and-gene-synthesis

Illumina’s instruments are now responsible for such a high percentage of sequencing output that the company is effectively setting prices for the entire industry. Illumina is being pushed by competition to increase performance, but this does not necessarily translate into lower prices. It doesn’t behoove Illumina to drop prices at this point, and we won’t see any substantial decrease until a serious competitor shows up and starts threatening Illumina’s market share. The absence of real competition is the primary reason sequencing prices have flattened out over the last couple of data points.

Note that the oligo prices above are for column-based synthesis, and that oligos synthesized on arrays are much less expensive. However, array synthesis comes with the usual caveat that the quality is generally lower, unless you are getting your DNA from Agilent, which probably means you are getting your dsDNA from Gen9.

Note also that the distinction between the price of oligos and the price of double-stranded sDNA is becoming less useful. Whether you are ordering from Life/Thermo or from your local academic facility, the cost of producing oligos is now, in most cases, independent of their length. That’s because the cost of capital (including rent, insurance, labor, etc) is now more significant than the cost of goods. Consequently, the price reflects the cost of capital rather than the cost of goods. Moreover, the cost of the columns, reagents, and shipping tubes is certainly more than the cost of the atoms in the sDNA you are ostensibly paying for. Once you get into longer oligos (substantially larger than 50-mers) this relationship breaks down and the sDNA is more expensive. But, at this point in time, most people aren’t going to use longer oligos to assemble genes unless they have a tricky job that doesn’t work using short oligos.

Looking forward, I suspect oligos aren’t going to get much cheaper unless someone sorts out how to either 1) replace the requisite human labor and thereby reduce the cost of capital, or 2) finally replace the phosphoramidite chemistry that the industry relies upon.

IDT’s gBlocks come at prices that are constant across quite substantial ranges in length. Moreover, part of the decrease in price for these products is embedded in the fact that you are buying smaller chunks of DNA that you then must assemble and integrate into your organism of choice.

Someone who has purchased and assembled an absolutely enormous amount of sDNA over the last decade, suggested that if prices fell by another order of magnitude, he could switch completely to outsourced assembly. This is a potentially interesting “tipping point”. However, what this person really needs is sDNA integrated in a particular way into a particular genome operating in a particular host. The integration and testing of the new genome in the host organism is where most of the cost is. Given the wide variety of emerging applications, and the growing array of hosts/chassis, it isn’t clear that any given technology or firm will be able to provide arbitrary synthetic sequences incorporated into arbitrary hosts.

 TrackBack URL: http://www.synthesis.cc/cgi-bin/mt/mt-t.cgi/397

 

Startup to Strengthen Synthetic Biology and Regenerative Medicine Industries with Cutting Edge Cell Products

28 Nov 2013 | PR Web

Dr. Jon Rowley and Dr. Uplaksh Kumar, Co-Founders of RoosterBio, Inc., a newly formed biotech startup located in Frederick, are paving the way for even more innovation in the rapidly growing fields of Synthetic Biology and Regenerative Medicine. Synthetic Biology combines engineering principles with basic science to build biological products, including regenerative medicines and cellular therapies. Regenerative medicine is a broad definition for innovative medical therapies that will enable the body to repair, replace, restore and regenerate damaged or diseased cells, tissues and organs. Regenerative therapies that are in clinical trials today may enable repair of damaged heart muscle following heart attack, replacement of skin for burn victims, restoration of movement after spinal cord injury, regeneration of pancreatic tissue for insulin production in diabetics and provide new treatments for Parkinson’s and Alzheimer’s diseases, to name just a few applications.

While the potential of the field is promising, the pace of development has been slow. One main reason for this is that the living cells required for these therapies are cost-prohibitive and not supplied at volumes that support many research and product development efforts. RoosterBio will manufacture large quantities of standardized primary cells at high quality and low cost, which will quicken the pace of scientific discovery and translation to the clinic. “Our goal is to accelerate the development of products that incorporate living cells by providing abundant, affordable and high quality materials to researchers that are developing and commercializing these regenerative technologies” says Dr. Rowley

 

Life at the Speed of Light

http://kcpw.org/?powerpress_pinw=92027-podcast

NHMU Lecture featuring – J. Craig Venter, Ph.D.
Founder, Chairman, and CEO – J. Craig Venter Institute; Co-Founder and CEO, Synthetic Genomics Inc.

J. Craig Venter, Ph.D., is Founder, Chairman, and CEO of the J. Craig Venter Institute (JVCI), a not-for-profit, research organization dedicated to human, microbial, plant, synthetic and environmental research. He is also Co-Founder and CEO of Synthetic Genomics Inc. (SGI), a privately-held company dedicated to commercializing genomic-driven solutions to address global needs.

In 1998, Dr. Venter founded Celera Genomics to sequence the human genome using new tools and techniques he and his team developed.  This research culminated with the February 2001 publication of the human genome in the journal, Science. Dr. Venter and his team at JVCI continue to blaze new trails in genomics.  They have sequenced and a created a bacterial cell constructed with synthetic DNA,  putting humankind at the threshold of a new phase of biological research.  Whereas, we could  previously read the genetic code (sequencing genomes), we can now write the genetic code for designing new species.

The science of synthetic genomics will have a profound impact on society, including new methods for chemical and energy production, human health and medical advances, clean water, and new food and nutritional products. One of the most prolific scientists of the 21st century for his numerous pioneering advances in genomics,  he  guides us through this emerging field, detailing its origins, current challenges, and the potential positive advances.

His work on synthetic biology truly embodies the theme of “pushing the boundaries of life.”  Essentially, Venter is seeking to “write the software of life” to create microbes designed by humans rather than only through evolution. The potential benefits and risks of this new technology are enormous. It also requires us to examine, both scientifically and philosophically, the question of “What is life?”

J Craig Venter wants to digitize DNA and transmit the signal to teleport organisms

https://pharmaceuticalintelligence.com/2013/11/01/j-craig-venter-wants-to-digitize-dna-and-transmit-the-signal-to-teleport-organisms/

2013 Genomics: The Era Beyond the Sequencing of the Human Genome: Francis Collins, Craig Venter, Eric Lander, et al.

https://pharmaceuticalintelligence.com/2013/02/11/2013-genomics-the-era-beyond-the-sequencing-human-genome-francis-collins-craig-venter-eric-lander-et-al/

Human Longevity Inc (HLI) – $70M in Financing of Venter’s New Integrative Omics and Clinical Bioinformatics

https://pharmaceuticalintelligence.com/2014/03/05/human-longevity-inc-hli-70m-in-financing-of-venters-new-integrative-omics-and-clinical-bioinformatics/

 

 

Where Will the Century of Biology Lead Us?

By Randall Mayes

A technology trend analyst offers an overview of synthetic biology, its potential applications, obstacles to its development, and prospects for public approval.

  • In addition to boosting the economy, synthetic biology projects currently in development could have profound implications for the future of manufacturing, sustainability, and medicine.
  • Before society can fully reap the benefits of synthetic biology, however, the field requires development and faces a series of hurdles in the process. Do researchers have the scientific know-how and technical capabilities to develop the field?

Biology + Engineering = Synthetic Biology

Bioengineers aim to build synthetic biological systems using compatible standardized parts that behave predictably. Bioengineers synthesize DNA parts—oligonucleotides composed of 50–100 base pairs—which make specialized components that ultimately make a biological system. As biology becomes a true engineering discipline, bioengineers will create genomes using mass-produced modular units similar to the microelectronics and computer industries.

Currently, bioengineering projects cost millions of dollars and take years to develop products. For synthetic biology to become a Schumpeterian revolution, smaller companies will need to be able to afford to use bioengineering concepts for industrial applications. This will require standardized and automated processes.

A major challenge to developing synthetic biology is the complexity of biological systems. When bioengineers assemble synthetic parts, they must prevent cross talk between signals in other biological pathways. Until researchers better understand these undesired interactions that nature has already worked out, applications such as gene therapy will have unwanted side effects. Scientists do not fully understand the effects of environmental and developmental interaction on gene expression. Currently, bioengineers must repeatedly use trial and error to create predictable systems.

Similar to physics, synthetic biology requires the ability to model systems and quantify relationships between variables in biological systems at the molecular level.

The second major challenge to ensuring the success of synthetic biology is the development of enabling technologies. With genomes having billions of nucleotides, this requires fast, powerful, and cost-efficient computers. Moore’s law, named for Intel co-founder Gordon Moore, posits that computing power progresses at a predictable rate and that the number of components in integrated circuits doubles each year until its limits are reached. Since Moore’s prediction, computer power has increased at an exponential rate while pricing has declined.

DNA sequencers and synthesizers are necessary to identify genes and make synthetic DNA sequences. Bioengineer Robert Carlson calculated that the capabilities of DNA sequencers and synthesizers have followed a pattern similar to computing. This pattern, referred to as the Carlson Curve, projects that scientists are approaching the ability to sequence a human genome for $1,000, perhaps in 2020. Carlson calculated that the costs of reading and writing new genes and genomes are falling by a factor of two every 18–24 months. (see recent Carlson comment on requirement to read and write for a variety of limiting  conditions).

Startup to Strengthen Synthetic Biology and Regenerative Medicine Industries with Cutting Edge Cell Products

https://pharmaceuticalintelligence.com/2013/11/28/startup-to-strengthen-synthetic-biology-and-regenerative-medicine-industries-with-cutting-edge-cell-products/

Synthetic Biology: On Advanced Genome Interpretation for Gene Variants and Pathways: What is the Genetic Base of Atherosclerosis and Loss of Arterial Elasticity with Aging

https://pharmaceuticalintelligence.com/2013/05/17/synthetic-biology-on-advanced-genome-interpretation-for-gene-variants-and-pathways-what-is-the-genetic-base-of-atherosclerosis-and-loss-of-arterial-elasticity-with-aging/

Synthesizing Synthetic Biology: PLOS Collections

https://pharmaceuticalintelligence.com/2012/08/17/synthesizing-synthetic-biology-plos-collections/

Capturing ten-color ultrasharp images of synthetic DNA structures resembling numerals 0 to 9

https://pharmaceuticalintelligence.com/2014/02/05/capturing-ten-color-ultrasharp-images-of-synthetic-dna-structures-resembling-numerals-0-to-9/

Silencing Cancers with Synthetic siRNAs

https://pharmaceuticalintelligence.com/2013/12/09/silencing-cancers-with-synthetic-sirnas/

Genomics Now—and Beyond the Bubble

Futurists have touted the twenty-first century as the century of biology based primarily on the promise of genomics. Medical researchers aim to use variations within genes as biomarkers for diseases, personalized treatments, and drug responses. Currently, we are experiencing a genomics bubble, but with advances in understanding biological complexity and the development of enabling technologies, synthetic biology is reviving optimism in many fields, particularly medicine.

BY MICHAEL BROOKS    17 APR, 2014     http://www.newstatesman.com/

Michael Brooks holds a PhD in quantum physics. He writes a weekly science column for the New Statesman, and his most recent book is The Secret Anarchy of Science.

The basic idea is that we take an organism – a bacterium, say – and re-engineer its genome so that it does something different. You might, for instance, make it ingest carbon dioxide from the atmosphere, process it and excrete crude oil.

That project is still under construction, but others, such as using synthesised DNA for data storage, have already been achieved. As evolution has proved, DNA is an extraordinarily stable medium that can preserve information for millions of years. In 2012, the Harvard geneticist George Church proved its potential by taking a book he had written, encoding it in a synthesised strand of DNA, and then making DNA sequencing machines read it back to him.

When we first started achieving such things it was costly and time-consuming and demanded extraordinary resources, such as those available to the millionaire biologist Craig Venter. Venter’s team spent most of the past two decades and tens of millions of dollars creating the first artificial organism, nicknamed “Synthia”. Using computer programs and robots that process the necessary chemicals, the team rebuilt the genome of the bacterium Mycoplasma mycoides from scratch. They also inserted a few watermarks and puzzles into the DNA sequence, partly as an identifying measure for safety’s sake, but mostly as a publicity stunt.

What they didn’t do was redesign the genome to do anything interesting. When the synthetic genome was inserted into an eviscerated bacterial cell, the new organism behaved exactly the same as its natural counterpart. Nevertheless, that Synthia, as Venter put it at the press conference to announce the research in 2010, was “the first self-replicating species we’ve had on the planet whose parent is a computer” made it a standout achievement.

Today, however, we have entered another era in synthetic biology and Venter faces stiff competition. The Steve Jobs to Venter’s Bill Gates is Jef Boeke, who researches yeast genetics at New York University.

Boeke wanted to redesign the yeast genome so that he could strip out various parts to see what they did. Because it took a private company a year to complete just a small part of the task, at a cost of $50,000, he realised he should go open-source. By teaching an undergraduate course on how to build a genome and teaming up with institutions all over the world, he has assembled a skilled workforce that, tinkering together, has made a synthetic chromosome for baker’s yeast.

 

Stepping into DIYbio and Synthetic Biology at ScienceHack

Posted April 22, 2014 by Heather McGaw and Kyrie Vala-Webb

We got a crash course on genetics and protein pathways, and then set out to design and build our own pathways using both the “Genomikon: Violacein Factory” kit and Synbiota platform. With Synbiota’s software, we dragged and dropped the enzymes to create the sequence that we were then going to build out. After a process of sketching ideas, mocking up pathways, and writing hypotheses, we were ready to start building!

The night stretched long, and at midnight we were forced to vacate the school. Not quite finished, we loaded our delicate bacteria, incubator, and boxes of gloves onto the bus and headed back to complete our bacterial transformation in one of our hotel rooms. Jammed in between the beds and the mini-fridge, we heat-shocked our bacteria in the hotel ice bucket. It was a surreal moment.

While waiting for our bacteria, we held an “unconference” where we explored bioethics, security and risk related to synthetic biology, 3D printing on Mars, patterns in juggling (with live demonstration!), and even did a Google Hangout with Rob Carlson. Every few hours, we would excitedly check in on our bacteria, looking for bacterial colonies and the purple hue characteristic of violacein.

Most impressive was the wildly successful and seamless integration of a diverse set of people: in a matter of hours, we were transformed from individual experts and practitioners in assorted fields into cohesive and passionate teams of DIY biologists and science hackers. The ability of everyone to connect and learn was a powerful experience, and over the course of just one weekend we were able to challenge each other and grow.

Returning to work on Monday, we were hungry for more. We wanted to find a way to bring the excitement and energy from the weekend into the studio and into the projects we’re working on. It struck us that there are strong parallels between design and DIYbio, and we knew there was an opportunity to bring some of the scientific approaches and curiosity into our studio.

 

 

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Combining Nanotube Technology and Genetically Engineered Antibodies to Detect Prostate Cancer Biomarkers[1]

Writer, Curator: Stephen J. Williams, Ph.D.

acs nanoFigure of  Carbon Nanotube Transistor design with functionalized antibodies for biomarker detection.  From paper of A.T. Johnson; used with permission from A.T. Johnson)

In a literature review of the current status of the breast cancer biomarker field[2], author Dr. Michael Duffy, from University College Dublin, pondered the clinical utility of breast cancer serum markers and suggested that due to lack of sensitivity and specificity none of available markers is of value for detection of early breast cancer however these biomarkers have been shown useful in monitoring patients with advanced disease. For instance high preoperative CA15-3 is indicative of adverse patient outcome.  According to American Society of Clinical Oncology Expert Panel, however CA 15-3 may lack the sensitivity and disease specificity for breast cancer as a prognostic marker.  For panel suggestions please click on the link below:

http://www.asco.org/sites/www.asco.org/files/breast_tm_2007_changes-final.pdf

The same panel also concurred on the lack of prognostic value of other markers (for example CEA for colon cancer) but did agree that 66-73% of patients with advanced disease, who responded to therapy, showed reduction in these serum markers.  Indeed, CA125, long associated as a biomarker for ovarian cancer, does not have the sensitivity and especially the disease specificity to be a stand-alone prognostic marker[3].  Therefore, although “omics” strategies have suggested multiple possible biomarkers  for various cancers, a major issue in translating a putative biomarker to either:

1)      a clinically validated (panel) of disease-relevant biomarkers or

2)      biomarkers useful for therapeutic monitoring

is obtaining the specificity and sensitivity for detection in bio-specimens.   As discussed below, this is being achieved with the merger of nanotechnology-based sensors and bioengineering of biomolecule.

For ASCO panel suggestions of biomarkers useful in Prostate cancer please see the link below:

http://jco.ascopubs.org/site/misc/specialarticles.xhtml#GENITOURINARY_CANCER

As a side note, since 2010, ASCO has focused on reviewing and producing new guidelines for cancer biomarkers including genome sequencing:

http://www.medscape.com/viewarticle/723349

Osteopontin (OPN) and prostate cancer

Osteopontin is a phosphorylated glycoprotein secreted by activated macrophages, leukocytes, activated T lymphocytes and is present at sites of inflammation (for a review of OPN see [4]).  Osteopontin interacts with several integrins and CD44 (a putative cancer stem cell marker).  Binding of OPN to cell integrins mediates cell-matrix and cell-cell communication, stimulating adhesion, migration (through interaction with urokinase plasminogen activator {uPA}) and cell signaling pathways such as the HGF-Met pathway.  Overexpression is found on a variety of cancers including breast, lung, colorectal, ovarian and melanoma[5].  And although OPN is detected in normal tissue, it is known that OPN over-expression can alter the malignant potential of tumor cells.

Roles of osteopontin in cancer include:

  • Binding to CD44
  • Increase in growth factor signaling (HGF/Met pathway)
  • Increase uPA activity- increase invasiveness
  • Angiogenesis thru binding with αvβ3 integrin and increased VEGF expression
  • Protection against apoptosis: OPN activates nuclear factor Κβ

Some researchers have suggested it could be a prognostic marker for breast and lung cancer while there have been conflicting reports as to whether OPN expression is correlated to malignant potential in prostate cancer[6].  Osteopontin is found on tumor infiltrating macrophages, which may contribute to OPN as a prognostic marker. Breast cancer patients (disseminated carcinomas) have 4-10 times higher serum levels of OPN than found in healthy patients, although there is no difference in pre- or post-menopausal women[7].

Piezoelectric sensors have been used by the same group at Fox Chase Cancer Center to detect serum levels of the HER2 protein in breast cancer patients, for the purpose of therapeutic monitoring after anti-HER2 antibody trastuzumab (Herceptin™) therapy.  Lina Loo, in the laboratory of Dr. Gregory Adams showed the utility of using (scFv) to trastuzumab (anti-HER2) with pizo-electric nanotubes to accurately and reproducibly determine levels of serum HER2[8].  This method improved the sensitivity of serum HER2 detection over other methods such as:

  • ELISA {enzyme-linked immunoassay}
  • Luminex platforms

Please watch the following video interview concerning genetically engineered scFV antibody fragments and their use in cancer detection and treatment (with Dr. Matt Robinson and Dr. Greg Adams, from Fox Chase Cancer Center)

PLEASE WATCH VIDEO

However the advent of nanotechnology-based detection system combined with engineered affinity-based biomolecules has increased both the sensitivity and specificity of biomarker detection from complex fluids such as plasma and urine.  The advent of multiple types of biosensors, including

has given the ability to measure, with enhanced sensitivity and specificity,  putative biomarkers of disease in minute volumes of precious bio-samples.

The basic design of a biosensor is made of three components:

  1. A recognition element (I.e. antibodies, nucleic acids, enzymes)
  2. A signal transducer (electrochemical, optical, piezoelectric)
  3. Signal processor (relays and displays)

In the journal ACS Nano Mitchel Lerner from Dr. Charlie Johnson’s laboratory at University of Pennsylvania in collaboration with Fox Chase Cancer researchers in the laboratory of Dr. Matthew Robinson, describe a piezoelectric detection system for quantifying levels of osteopontin (OPN), a putative biomarker for prostate cancer[1].  In this paper Dr. Robinson’s group at Fox Chase, genetically engineered a single chain variable fragment (scFv) protein {the binding portion of the antibody} which had high affinity for OPN.  This scFv was attached to a carbon nanotube field-effect transistor (NT-FET), designed by Dr. Johnson’s group, using a chemical process called chemical functionalization {a process using diazonium salts to covalently attach scFV to NT-FET.

functionalization

Figure. Functionalization scheme for OPN attachment to carbon nanotubes. As figure 1 legend in paper states: “First, sp8 hybridized-sites are created o the nanotube sidewall by incubation in a diazonium salt solution.  The carboxylic acid group is then activated by EDC and stabilized with NHS.ScFv antibody displaces the NHS and forms an amide bond.  OPN epitope is shown in yellow and the C and N-terminuses are in orange and green respectively.” (used by permision for A.T. Charlie Johnson)

This system was then used to determine the selectivity and sensitivity of OPN from complex solutions.

Methods: 

Nanotube (NT) design

  • Grown by catalytic vapor deposition
  • Electrical contacts patterned using photo-lithography
  • Atomic Force microscopy was used to verify structure of nanotube

Chemical Linking of scFv to nanotube

  • Diazonium treatment resulted in activation and subsequent stabilization of amino (NHS) side chain
  • Amine group on lysine of scFV displaced NHS group => covalent attachment of scFV to NT
  • Atomic Force Spectroscopy used to verify linkage of scFv to nanotube

Results showed there was

  • minimal non-specific binding of OPN to the scFv
  • system allowed for detection limit of 1 pg/ml OPN (pictogram/milliliter) or 30 fM (fentomolar) in a phosphate buffered saline solution.
  •  Only a minute volume (10 µl) of sample is needed
  • Sensor able to measure million-fold  range of OPN concentrations ( from 10-3 to 103 ng/mL OPN)

Two experiments were conducted to determine the specificity of OPN to the antibody-detection system.

1st experiment

–          scFv functionalized  sensor was incubated in a solution of high concentration of BSA (450 mg/ml) to approximate nonspecific proteins in patient samples

–           minimal signal was detected

        2nd experiment

–          Functionalized NT-FET devices with a scFv based on the HER2 therapeutic antibody trastuzumab

–          There was no binding of OPN to anti-HER2 devices

–          Therefore anti OPN (23C3) scFv-functionalized carbon nanotube sensors exhibit high levels of specificity to OPN

The authors conclude “the functionalization procedure described here is expected to be generalizable to any antibody containing an accessible amine group, and to result in biosensors appropriate for detection of corresponding complementary proteins at fM concentrations”.

I had the opportunity to speak with co-author Dr. Matthew Robinson, Assistant Professor in the Developmental Therapeutics Program at Fox Chase Cancer Center about the next steps for this work.  Dr. Robinson mentioned that “at this point we have not looked in patient samples yet but our plan is to move in that direction. We need to establish sensitivity/specificity in increasingly complex samples (e.g. spiked normal serum and retrospectively in patient serum with known levels of biomarkers).” 

Cancer patients often present a complex metabolic profile.  The paper notes that OPN has a pI (isoelectric point) of 4.2, which would result in a negative charge at physiologically normal pH of 7.6. I asked Dr. Robinson about if changes in metabolic profile could hinder OPN binding to the NT-FET system would require some preprocessing of blood samples.  Dr. Robinson  agreed “that confounding variables such as additional diseases but even things like diet (i.e. is fasting necessary) need to be addressed before this platform is ready for use in clinical setting.
It is likely that sample prep will be needed to remove albumin, lower salt concentrations, etc. This could end up being problematic for biomarkers that are unstable and would degrade over the time necessary for sample prep. It is also possible that sample prep to remove albumin and other background factors could result in loss of biomarkers. This will need to be determined on a case-by-case basis with validated testing methods.”
One useful advantage of this system is the possibility of measuring multiple biomarkers, clinically important as studies has suggested that

multiple markers result in the higher sensitivity/specificity for many infrequent cancers, such as ovarian. Dr. Robinson agrees “that panels of biomarkers are likely to be better at early detection and diagnosis. In principle the platform that we describe can be set up to allow for detection of  multiple biomarkers at a time. From the biology end of things we have built antibodies against 3 different prostate cancer biomarkers for that purpose.”

Dr. Johnson  commented on the ability of the platform allowed for the simultaneous detection of multiple biomarkers, noting that ”the platform is compatible with the measurement of multiple biomarkers through the use of multiple devices, each functionalized with their own antibody.”

 

ASCO guidelines Expert Panel on Tumor Biomarkers 2007 Update for Breast Cancer:

http://www.asco.org/sites/www.asco.org/files/breast_tm_2007_changes-final.pdf 

ASCO Guidelines for Genitourinary Cancer:

Screening for Prostate Cancer With Prostate-Specific Antigen Testing: American Society of Clinical Oncology Provisional Clinical Opinion

Published in JCO, Vol. 30, Issue 24 (August 20), 2012: 3020-3025

American Society of Clinical Oncology Clinical Practice Guideline on Uses of Serum Tumor Markers in Adult Males With Germ Cell Tumors

Published in JCO, Vol 28, Issue 20 (July 10), 2010: 3388-3404

American Society of Clinical Oncology Endorsement of the Cancer Care Ontario Practice Guideline on Nonhormonal Therapy for Men With Metastatic Hormone-Refractory (castration-resistant) Prostate Cancer

Published in JCO, Vol 25, Issue 33 (November 20), 2007: 5313-5318

Initial Hormonal Management of Androgen-Sensitive Metastatic, Recurrent, or Progressive Prostate Cancer: 2006 Update of an American Society of Clinical Oncology Practice Guideline

Published in JCO, Vol. 25, Issue 12 (April 20), 2007: 1596-1605

References:

1.            Lerner MB, D’Souza J, Pazina T, Dailey J, Goldsmith BR, Robinson MK, Johnson AT: Hybrids of a genetically engineered antibody and a carbon nanotube transistor for detection of prostate cancer biomarkers. ACS nano 2012, 6(6):5143-5149.

2.            Duffy MJ: Serum tumor markers in breast cancer: are they of clinical value? Clinical chemistry 2006, 52(3):345-351.

3.            Meyer T, Rustin GJ: Role of tumour markers in monitoring epithelial ovarian cancer. British journal of cancer 2000, 82(9):1535-1538.

4.            Rodrigues LR, Teixeira JA, Schmitt FL, Paulsson M, Lindmark-Mansson H: The role of osteopontin in tumor progression and metastasis in breast cancer. Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology 2007, 16(6):1087-1097.

5.            Brown LF, Berse B, Van de Water L, Papadopoulos-Sergiou A, Perruzzi CA, Manseau EJ, Dvorak HF, Senger DR: Expression and distribution of osteopontin in human tissues: widespread association with luminal epithelial surfaces. Molecular biology of the cell 1992, 3(10):1169-1180.

6.            Thoms JW, Dal Pra A, Anborgh PH, Christensen E, Fleshner N, Menard C, Chadwick K, Milosevic M, Catton C, Pintilie M et al: Plasma osteopontin as a biomarker of prostate cancer aggression: relationship to risk category and treatment response. British journal of cancer 2012, 107(5):840-846.

7.            Brown LF, Papadopoulos-Sergiou A, Berse B, Manseau EJ, Tognazzi K, Perruzzi CA, Dvorak HF, Senger DR: Osteopontin expression and distribution in human carcinomas. The American journal of pathology 1994, 145(3):610-623.

8.            Loo L, Capobianco JA, Wu W, Gao X, Shih WY, Shih WH, Pourrezaei K, Robinson MK, Adams GP: Highly sensitive detection of HER2 extracellular domain in the serum of breast cancer patients by piezoelectric microcantilevers. Analytical chemistry 2011, 83(9):3392-3397.

Other posts from this site on Biomarkers, Cancer, and Nanotechnology include:

Stanniocalcin: A Cancer Biomarker.

Mesothelin: An early detection biomarker for cancer (By Jack Andraka)

Squeezing Ovarian Cancer Cells to Predict Metastatic Potential: Cell Stiffness as Possible Biomarker

PIK3CA mutation in Colorectal Cancer may serve as a Predictive Molecular Biomarker for adjuvant Aspirin therapy

Biomarker tool development for Early Diagnosis of Pancreatic Cancer: Van Andel Institute and Emory University

Early Biomarker for Pancreatic Cancer Identified

In Search of Clarity on Prostate Cancer Screening, Post-Surgical Followup, and Prediction of Long Term Remission

Prostate Cancer Molecular Diagnostic Market – the Players are: SRI Int’l, Genomic Health w/Cleveland Clinic, Myriad Genetics w/UCSF, GenomeDx and BioTheranostics

Early Detection of Prostate Cancer: American Urological Association (AUA) Guideline

A Blood Test to Identify Aggressive Prostate Cancer: a Discovery @ SRI International, Menlo Park, CA

Prostate Cancer Cells: Histone Deacetylase Inhibitors Induce Epithelial-to-Mesenchymal Transition

Prostate Cancer and Nanotecnology

 

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Reported by: Dr. Venkat S. Karra, Ph.D.

“Comprehensive computer models of entire cells have the potential to advance our understanding of cellular function and, ultimately, to inform new approaches for the diagnosis and treatment of disease.” Not only does the model allow researchers to address questions that aren’t practical to examine otherwise, it represents a stepping-stone towards its use  in bioengineering and medicine.

A team led by Stanford bioengineering Professor Markus Covert used data from more than 900 scientific papers to account for every molecular interaction that takes place in the life cycle of Mycoplasma genitalium. Mycoplasma genitalium is a humble parasitic bacterium, known mainly for showing up uninvited in human urogenital and respiratory tracts. But the pathogen also has the distinction of containing the smallest genome of any free-living organism – only 525 genes, as opposed to the 4,288 of E. coli, a more traditional laboratory bacterium.

“This is potentially the new Human Genome Project,” Karr said who is a co-first author and Stanford biophysics graduate student. “It’s to understand biology generally.”

“It’s going to take a really large community effort to get close to a human model.”

This is a breakthrough effort for computational biology, the world’s first complete computer model of an organism. “This achievement demonstrates a transforming approach to answering questions about fundamental biological processes,” said James M. Anderson, director of the National Institutes of Health Division of Program Coordination, Planning, and Strategic Initiatives.

Study results were published by Stanford researchers in the journal Cell.

The research was partially funded by an NIH Director’s Pioneer Award from the National Institute of Health Common Fund.

Source:

http://www.dddmag.com/news/2012/07/first-complete-computer-model-bacteria?et_cid=2783229&et_rid=45527476&linkid=http%3a%2f%2fwww.dddmag.com%2fnews%2f2012%2f07%2ffirst-complete-computer-model-bacteria

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