Cell-Transistor-Hybrid

Biological cells are able to receive, process, and transmit information.
Connecting these cells to micro-electronic circuits opens up exciting new perspectives in bioelectronics, information technology, medical engineering and in sensor development. Living cells possess receptors of unmatched sensitivity that detect external signals of chemical nature (nutrients, hormones, neurotransmitters, changes in proton- or ion-concentration, etc.) or physical stimuli as a change in temperature, light, mechanical force, or even electromagnetic fields. These input parameters are processed by the cells. The internal “machinery” of the cell
includes signal amplification cascades and logic connections of high non-linearity, but the details remain to be unveiled. The resulting output signal may generate many physiological reactions inside the cell, as the synthesis of specific olecules, a change in gene expression or the storage of certain substances.
The output signals also allow the cell to communicate with its environment and with other cells. In order to provide selective long-term cell-transducer interfaces in vitro, microtechnology is used for the development of planar arrays with large numbers of field-effect transistors or metal electrodes in the size of the individual cells. These arrays usually consist of a culture chamber with embedded chip. For metalelectrode arrays (MEAs), insulated conductor paths are patterned lithographically. Their opened metallic ends form the sensing electrodes. In addition, field-effect transistor (FET) arrays have been developed to record the electrical signals from cells. Modifications of standard FET fabrication processes lead to devices with metal-free gate electrodes. A variation of these devices is the so-called ion-sensitive field-effect transistor (ISFET). Its gate dielectric is modified to yield higher sensitivity for certain ions. Sufficient electrical coupling between the cell and the electrode for extracellular signal recording is achieved only if a cell or a part of a cell is located directly on top of the electrode.

Silicon-based Biochemical Sensors

Silicon-based microelectronics represents the platform of our modern information technology. In recent years, silicon technology has been utilized to couple data processing systems to chemical and biological structures, integrating ion-selective materials and simple biomolecules or even cells and cell systems. The main advantage of these (bio-)chemical sensors is the high sensitivity and selectivity of their chemical and biological component as well as the possibility of miniaturization down to the nanometer scale. (Bio-)chemical sensors have been developed as rugged and reliable devices for the rapid and quantitative detection of specific analytes. For example, enzymes allow to monitor the blood glucose concentration of diabetic patients, a pH electrode may adjust the proper fermentation routine for cheese
production and sensors and catalysts control the car pollution. (Bio-)chemical sensors constitute an interdisciplinary interface between the environment and data processing systems. Moreover, because these sensors can be designed in a modular concept, the combination of single sensors to sensor arrays is possible. We present some examples of new silicon-based (bio-) chemical sensors, which have been developed in a collaboration between ISG (FZJ) and the University of Applied Sciences Aachen (Jülich division): • capacitive field-effect sensors as a combination of ionophores or enzymes and silicon technology, • a silicon-based multi-parameter hybrid ion-sensitive FET (ISFET) module suitable for sensor arrays, • a beetle/chip biologically sensitive field-effect transistor (BioFET) as a first step towards a bioelectronic device with extraordinary sensory abilities. All described (bio-)chemical sensors utilize the field effect to transfer the detected (bio-) hemical information to an electrical signal.

Electrical activity of cells

Cells form a membrane potential between the interior of the cell and the surrounding liquid. This po-tential normally has a value of -60 mV to –90 mV and is caused by an inhomogeneous distribution of ions and the different permeability of the membrane to these ions. The active transport of potassium and sodium ions into and out of the cell, respectively, is accom-plished by a number of sodium-potassium pumps scattered across the cell membrane (compare Figure 2). Each pump transports two ions of potassium into the cell for every three ions of sodium pumped out. This establishes a particular distribution of positively charged ions across the cell membrane, with more sodium present outside the cell than inside, and more potassium inside the cell than outside. The simplest way to derive an expression for the membrane potential assumes a system in thermody-namic equilibrium. This means that the electrochemical potential inside and outside the cell is equal. Therefore, however, an unhindered exchange through the permeable membrane has to be possible.

What is artificial life?(synthetic biology)

To the untrained eye, the tiny, misshapen, fatty blobs on Giovanni Murtas's microscope slide would not look very impressive. But when the Italian scientist saw their telltale green fluorescent glint he knew he had achieved something remarkable - and taken a vital step towards building a living organism from scratch.

The green glow was proof that his fragile creations were capable of making their own proteins, a crucial ability of all living things and vital for carrying out all other aspects of life.

Though only a first step, the discovery will hasten efforts by scientists to build the world's first synthetic organism. It could also prove a significant development in the multibillion-dollar battle to exploit the technology for manufacturing commercially valuable chemicals such as drugs and biofuels or cleaning up pollution.

The achievement is a major advance for the new field of "synthetic biology". Its proponents hope to construct simple bespoke organisms with carefully chosen components. But some campaigners worry about the new technology's unsettling potential and argue there should be a moratorium on the research until the ethical and technological implications have been discussed more widely.

One of the field's leading lights is the controversial scientist Craig Venter, a beach bum turned scientific entrepreneur who is better known for sequencing the human genome and scouring the oceans for unknown genes on his luxury research yacht. The research institute he founded hopes to create an artificial "minimal organism". And he believes there is big money at stake.

In an interview with Newsweek magazine earlier this year, Dr Venter claimed that a fuel-producing microbe could become the first billion- or trillion-dollar organism. The institute has already patented a set of genes for creating such a stripped-down creature.

Ultimately, synthetic biologists hope to create the most efficient form of life possible, with the fewest genes needed to allow the organism to grow, replicate and proliferate. But researchers have approached the problem from two radically different directions. Dr Venter's team is starting with one of the simplest forms of cellular life known to science - the bacterium Mycoplasma genitalium, which causes urinary tract infections. By stripping out each of its 482 genes and observing the effect on the organism they have calculated that a core of 381 are vital for life.

In contrast to this top-down approach, Dr Murtas, at the Enrico Fermi research centre at Roma Tre University in Italy, and Pier Luigi Luisi aim to build a living thing from the bottom up. "The bottom-up approach has the possibility of creating living systems from entirely non-living materials," said Tom Knight, an expert in synthetic biology at the Massachusetts Institute of Technology.

"That's the real power of synthetic biology ... If you can take it apart into little bits and pieces and shuffle things around and put it back together and it still works, you can have much more confidence that you really understand what is going on."

The Italian team's advance is to make simple cells which are essentially bags made up of a fatty membrane containing just 36 enzymes and purified ribosomes - microscopic components common to all cells which translate the genetic code into protein. The primitive cells are capable of manufacturing protein from one gene.

The team chose a fluorescent green protein found in jellyfish because it was easy to see, using a microscope, when the protein is being made. "We are trying to minimise any system we put in place for the cell," said Dr Murtas. "We can prove at this point that we can have protein synthesis with a minimum set of enzymes - 36 at the moment." He hopes the project will teach him about the earliest stirrings of life in Earth's primeval slime some 3.5bn years ago.

"It's impressive work," said Prof Knight. "Protein synthesis is a wonderful place to start, partly because it is so well understood and ... you can figure out what is going wrong relatively easily. But there is a lot more involved in making cells that are alive ... I think the bottom-up people have a long way to go."

Dr Murtas acknowledges that his bags of enzymes are a long way from a fully functioning cell, but it is an important proof of principle - being able to make proteins is key for the cell to acquire new functions. Giving it the ability to grow, divide, partition components into daughter cells correctly and replicate DNA will be a major challenge, though. The team will report the work in the journal Biochemical and Biophysical Research Communications.

Dr Murtas is now working on making cells which are capable of division - crucial if they are to be truly alive. As the membrane grows, the team hope it will reach a point where the cell becomes too big and so gives rise to a pair of daughter cells.

In June, Dr Venter's research team announced that they had discovered how to carry out a "genome transplant". They showed they could move the genetic recipe of one species of Mycoplasma bacterium into another closely related species.

Artificial Cell Energy..

Professor Hywel Morgan at the University's School of Electronics & Computer Science (ECS) and Dr Peter Roach at the School of Chemistry and their team have received a European grant (€450k) to create a system that can detect single molecules in biological solutions.

They are using variants of molecules found in biology and creating 'senses' from electrical charges caused by the binding of the molecules to mimic the human nose. With this approach, the sensitivity of the device can be a thousand times better than the currently available electronic nose.

The receptors, which will be housed within an artificial membrane, remain in a closed steady state until approached by smell molecules, when they will open and transmit an electrical signal which will indicate the nature of the odour.

Professor Morgan comments: "Many medical diseases involve odour. A device such as ours could measure different hormones, diagnose diseases and even sniff for traces of explosives. Most odours are still mapped by humans. If we can find a way to replace this function with technology, we could use odour detection in many new areas."

Scientists are developing the world's smallest, high-performance and low-power sensor in silicon which will have applications in biosensing and environmental.

PCR primers sequences

Human papillomavirus (HPV) capture probe and PCR primers sequences.
6 capture CAG AAT TGG TGT ATG TGG AAG A(N152)
11 capture TAA TCT GAA TTA GTG TAT GTA GCA GAT TTA GAC A(N152)
16 capture GTA GTT TCT GAA GTA GAT ATG G(N152)
18 capture TGG TAG CAT CAT ATT GCC CAG G(N152)
26 capture ATC AGA TGG TTT AAA TGG AGT GGA TGC(N152)
31 capture TAC TAC TTT TAA ATG TAG TAT CAC(N152)
35 capture ACT GTC ACT AGA AGA CAC AGC AGA ACA CA(N152)
40 capture GGG GGA CTG TGT GGC ACC A(N152)
42 capture AGC AGC TGT ATA TGT ATC ACC AGA TGT TGC AGT GGC TCA(N152)
45 capture CTT AGT AGG GTC ATA TGT ACT TGG C(N152)
51 capture TTG GGG AAA CCG CAG CAG TGG CAG GGC TA(N152)
52 capture TAT GTG CTT TCC TTT TTA ACC T(N152)
54 capture GTC AGA ATT ATT AAA GCT ATC CTG CG(N152)
56 capture TTT TCG TGC ATC ATA TTT ACT TA(N152)
58 capture GTA CCT TCC TTA GTT ACT TCA G(N152)
59 capture CTG GTA GGT GTG TAT ACA TTA G(N152)
66 capture CAC GGG CAT CAT ATT TAG TTA A(N152)
68 capture TTA AAT TTA TTA GGA TCA TAA ATA TTT GGT A(N152)
82 capture AAT GTT TGT GCA ACA GAT TGA GTA ACA GCT GTG(N152)
83 capture GTT AGA GGC TGT GTA TTC ATT AGC(N152)
84 capture GGT TTA TAT TCT GAT TCG GTG T(N152)
globin capture AGC AAT AGA TGG CTC TGC CC(N152)
globin primer GAA GAG CCA AGG ACA GGT AC
globin rev primer BIOTIN CAA CTT CAT CCA CGT TCA CC
HMB01 rev primer BIOTIN GCG ACC CAA TGC AAA TTG GT
PGMY09F primer BIOTIN CGT CCC AAA GGA AAC TGA TC
PGMY09G primer BIOTIN CGA CCT AAA GGA AAC TGA TC
PGMY09H primer BIOTIN CGT CCA AAA GGA AAC TGA TC
PGMY09I primer BIOTIN GCC AAG GGG AAA CTG ATC
PGMY09J primer BIOTIN CGT CCC AAA GGA TAC TGA TC
PGMY09K primer BIOTIN CGT CCA AGG GGA TAC TGA TC
PGMY09L primer BIOTIN CGA CCT AAA GGG AAT TGA TC
PGMY09M primer BIOTIN CGA CCT AGT GGA AAT TGA TC
PGMY09N primer BIOTIN CGA CCA AGG GGA TAT TGA TC
PGMY09P primer BIOTIN GCC CAA CGG AAA CTG ATC
PGMY09Q primer BIOTIN CGA CCC AAG GGA AAC TGG TC
PGMY09R primer BIOTIN CGT CCT AAA GGA AAC TGG TC
PGMY11A primer GCA CAG GGA CAT AAC AAT GG
PGMY11B primer GCG CAG GGC CAC AAT AAT GG
PGMY11C primer GCA CAG GGA CAT AAT AAT GG
PGMY11D primer GCC CAG GGC CAC AAC AAT GG
PGMY11F primer GCT CAG GGT TTA AAC AAT GG

HPV - DNA COADING

Table 2: HPV type and signal probe sequence.
6 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TGT AGT TAC GGA TGC AC
11 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) CAG ATG CAG ATA GTG TCA T
16 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) CAG CGC ATA ATG ACA TAT TT
18 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TAC AGG AGA CTG TGT AG
26 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) AGA TGC TGT AGA TAA TGT AC
31 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TGT TTG CAA TTG CAG CA
35 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) CAG ACA TAT TTG TTC TAC GG
40 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TAA GGT TAA ATT AGT GCA ACG A
42 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) CAA AGA CAT GTT AGT ACT AC
45 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) ACA GGA TTT TGT GTA GAG G
51 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) ATA GTT AAA TTT GTA CTT CTG G
52 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) CAG CAC ATA AAG TCA TG
54 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TGG ATG CTG TAG CAC AC
56 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) ACT GTT CTG TAG CAG TAC T
58 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TGC ATA ATG TCA TAT TAG TG
59 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) GAA TAG AAG AAG TAG TAG AA
66 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TGT GCT TTT AGC TGC AT
68 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) CAG CTG ATT CAG TAG TAG TA
82 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) CTA ATG GTT AAA TTG GTA GTT
83 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) CTG TGT AGC AGG AGC TGA AA
84 (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TGG TAG CAG CAC TAA TA
Globin (N6) C(N6) G(N6) C(N6) GCT TA(N6) C(N6) G(N6) C(N6) TGA CTT TTA TGC CCA GAC CTG G
Table 3: HPV type and target mimic oligonucleotide sequences
6 ACC ACA CGC AGT ACC AAC ATG ACA TTA TGT GCA TCC GTA ACT ACA TCT TCC ACA TAC ACC AAT TCT GAT TAT AAA
11 GTA CAA ATA TGA CAC TAT GTG CAT CTG TGT CTA AAT CTG CTA CAT ACA CTA ATT CAG ATT ATA AGG AAT ACA TGC G
16 ACT ACA CGC AGT ACA AAT ATG TCA TTA TGT GCT GCC ATA TCT ACT TCA GAA ACT ACA TAT AAA AAT ACT AAC TTT AA
18 ACC ACT CCC AGT ACC AAT TTA ACA ATA TGT GCT TCT ACA CAG TCT CCT GTA CCT GGG CAA TAT GAT GCT ACC AAA T
26 GTA CTA ACC TTA CCA TTA GTA CAT TAT CTG CAG CAT CTG CAT CCA CTC CAT TTA AAC CAT CTG ATT ATA AAC AAT T
31 ACC ACA CGT AGT ACC AAT ATG TCT GTT TGT GCT GCA ATT GCA AAC AGT GAT ACT ACA TTT AAA AGT AGT AAT TTT AA
35 TGT AGT TGA TAC AAC CCG TAG TAC AAA TAT GTC TGT GTG TTC TGC TGT GTC TTC TAG TGA CAG TAC ATA TAA AAA T
40 AGT TGT AGA CAC CAC TCG TAG CAC TAA TTT AAC CTT ATG TGC TGC CAC ACA GTC CCC CAC ACC AAC CCC ATA TAA T
42 ACT ACC CGT AGT ACT AAC ATG ACT TTG TGT GCC ACT GCA ACA TCT GGT GAT ACA TAT ACA GCT GCT AAT TTT AAG G
45 AAC ATT ATG TGC CTC TAC ACA AAA TCC TGT GCC AAG TAC ATA TGA CCC TAC TAA GTT TAA GCA GTA TAG TAG ACA T
51 GTT GAT ACT ACC AGA AGT ACA AAT TTA ACT ATT AGC ACT GCC ACT GCT GCG GTT TCC CCA ACA TTT ACT CCA AGT A
52 ACC ACT CGT AGC ACT AAC ATG ACT TTA TGT GCT GAG GTT AAA AAG GAA AGC ACA TAT AAA AAT GAA AAT TTT AAG
54 GTA CTA ACC TAA CAT TGT GTG CTA CAG CAT CCA CGC AGG ATA GCT TTA ATA ATT CTG ACT TTA GGG AGT ATA TTA G
56 GTA CTA ACA TGA CTA TTA GTA CTG CTA CAG AAC AGT TAA GTA AAT ATG ATG CAC GAA AAA TTA ATC AGT ACC TTA G
58 ACC ACT CGT AGC ACT AAT ATG ACA TTA TGC ACT GAA GTA ACT AAG GAA GGT ACA TAT AAA AAT GAT AAT TTT AAG
59 ACT ACT CGC AGC ACC AAT CTT TCT GTG TGT GCT TCT ACT ACT TCT TCT ATT CCT AAT GTA TAC ACA CCT ACC AGT
66 ACT ACC AGA AGC ACC AAC ATG ACT ATT AAT GCA GCT AAA AGC ACA TTA ACT AAA TAT GAT GCC CGT GAA ATC AAT
68 GTA CCA ATT TTA CTT TGT CTA CTA CTA CTG AAT CAG CTG TAC CAA ATA TTT ATG ATC CTA ATA AAT TTA AGG AAT A
82 ACT ACT AGA AGT ACC AAT TTA ACC ATT AGC ACT GCT GTT ACT CAA TCT GTT GCA CAA ACA TTT ACT CCA GCA AAC T
83 GTA CCA ATA TTA CTA TTT CAG CTG CTG CTA CAC AGG CTA ATG AAT ACA CAG CCT CTA ACT TTA AGG AAT ACC TCC G
84 ACC ACC CGC AGC ACC AAT TTT ACT ATT AGT GCT GCT ACC AAC ACC GAA TCA GAA TAT AAA CCT ACC AAT TTT AAG
globin GGG AGG GCA GGA GCC AGG GCT GGG CAT AAA AGT CAG GGC AGA GCC ATC TAT TGC TTA CAT TTG CTT CTG ACA CAA C

HPV Leavel

Many of the HPV target mimics tested resulted in a specific
signal, with the exception of HPV types 16, 26, 35, 40, 42,
51, 52, and 82. This nonspecific hybridization signal generally
resulted from a long stretch of complementary
sequences (6–8 bases) among the HPV types due to their
close genetic relatedness. Nonspecific hybridization was
eliminated by introducing a mismatched base to the complementary
region in the signal probes for HPV types 16,
26, 35, 42, and 82 and the capture probes for HPV types
40, 42, 51, 52, and 82. For instance, the HPV 16 signal
probe hybridized with both the HPV 16 target mimic (Fig.
3, left panel) and the HPV 52 capture probe (Fig. 3, center
panel). This cross-reactivity was eliminated by changing
the second A base in the 5'-end of signal probe to a G base
(Fig. 3, right panel). In addition, we demonstrated that
one base modification of the signal probe (Fig. 3, left and
right panels) generated minimal negative impact to the
assay signal level.

BIO-ELECTRONIC

Two chips were spotted with capture probes consisting of DNA oligonucleotide sequences

specific for HPV types. Electrically conductive signal probes were synthesized to be

complementary to a distinct region of the amplified HPV target DNA. A portion of the HPV L1

region that was amplified by using consensus primers served as target DNA. The amplified

target was mixed with a cocktail of signal probes and added to a cartridge containing a DNA

chip to allow for hybridization with complementary capture probes.
Results

Two bioelectric chips were designed and successfully detected 86% of the HPV types contained

in clinical samples.
Conclusions

This model system demonstrates the potential of the eSensor platform for rapid and

integrated detection of multiple pathogens.

BioElectronic Will Chance Our Lifestyle......

Global emergence of pathogenic infectious diseases by both natural and intentional means

presents a formidable challenge to infectious disease surveillance and response, namely

timely and efficient pathogen detection. Many laboratory methods exist for identifying

pathogens, but most require exquisite care in sample handling and processing prior to

characterization of a pathogen. In addition, costly and perishable reagents, equipment, and

supplies are required for sensitive and specific detection. The ideal detection system would

integrate sample processing and pathogen characterization into a single automated device

that would eliminate laborious, and time consuming sample processing and costly detection.

Bioelectronic detection of nucleic acids on a miniature solid support is one of the first

steps toward development of such an integrated detection device.