Catalysis and specifically autocatalysis are the quintessential building blocks of life. Yet, although autocatalytic networks are necessary, they are not sufficient for the emergence of life-like properties, such as replication and adaptation. The ultimate and potentially fatal threat faced by molecular replicators is parasitism; if the polymerase error rate exceeds a critical threshold, even the fittest molecular species will disappear. Here we have developed an autocatalytic RNA early life mathematical network model based on enzyme kinetics, specifically the steady-state approximation. We confirm previous models showing that these second-order autocatalytic cycles are sustainable, provided there is a sufficient nucleotide pool. However, molecular parasites become untenable unless they sequentially degenerate to hyperparasites (i.e. parasites of parasites). Parasite resistance-a parasite-specific host response decreasing parasite fitness-is acquired gradually, and eventually involves an increased binding affinity of hyperparasites for parasites. Our model is supported at three levels; firstly, ribozyme polymerases display Michaelis-Menten saturation kinetics and comply with the steady-state approximation. Secondly, ribozyme polymerases are capable of sustainable auto-amplification and of surmounting the fatal error threshold. Thirdly, with growing sequence divergence of host and parasite catalysts, the probability of self-binding is expected to increase and the trend towards cross-reactivity to diminish. Our model predicts that primordial host-RNA populations evolved via an arms race towards a host-parasite-hyperparasite catalyst trio that conferred parasite resistance within an RNA replicator niche. While molecular parasites have traditionally been viewed as a nuisance, our model argues for their integration into the host habitat rather than their separation. It adds another mechanism-with biochemical precision-by which parasitism can be tamed and offers an attractive explanation for the universal coexistence of catalyst trios within prokaryotes and the virosphere, heralding the birth of a primitive molecular immunity.

The rapid detection and identification of infectious pathogens are a critical need for healthcare in both developed and developing countries. There is a need for portable diagnostics and epidemiological surveillance systems that can be deployed in remote field settings for infectious diseases testing, such as pandemic "hotspots" in Africa or southeast Asia. Together with the Vital-IT and Swiss-Prot groups, we developed a fast pathogen detection embedded hardware accelerator (no bigger than 75x50mm) capable of analyzing up to 250Mnt/s of DNA sequence. To deploy this solution, an embedded DNA Next Generation Sequencer (NGS) is used for retrieving the genetic material from patient's sample at the point of care (e.g., the Oxford Nanopore Technologies MinION). Successively, the collected DNA sequences are analized in order to detect the presence of known pathogen patterns. Currently, up to 100 different pathogens can be analized at the same time using one single embedded accelerator. Due to the low-power consumption of this hardware accelerator, it is possible to give access to worldwide health organizations and local administrations to a complete real-time embedded and battery powered surveillance solution. Moreover, this solution can greatly scale to big computing clusters, where a larger pathogens number can be analized in parallel, outperforming current state of art computationally expensive solutions.

BACKGROUND: Zinc Finger Nucleases (ZFNs) are man-made restriction enzymes useful for manipulating genomes by cleaving target DNA sequences. ZFNs allow therapeutic gene correction or creation of genetically modified model organisms. ZFN specificity is not absolute; therefore, it is essential to select ZFN target sites without similar genomic off-target sites. It is important to assay for off-target cleavage events at sites similar to the target sequence. RESULTS: ZFN-Site is a web interface that searches multiple genomes for ZFN off-target sites. Queries can be based on the target sequence or can be expanded using degenerate specificity to account for known ZFN binding preferences. ZFN off-target sites are outputted with links to genome browsers, facilitating off-target cleavage site screening. We verified ZFN-Site using previously published ZFN half-sites and located their target sites and their previously described off-target sites. While we have tailored this tool to ZFNs, ZFN-Site can also be used to find potential off-target sites for other nucleases, such as TALE nucleases. CONCLUSIONS: ZFN-Site facilitates genome searches for possible ZFN cleavage sites based on user-defined stringency limits. ZFN-Site is an improvement over other methods because the FetchGWI search engine uses an indexed search of genome sequences for all ZFN target sites and possible off-target sites matching the half-sites and stringency limits. Therefore, ZFN-Site does not miss potential off-target sites.

BACKGROUND: Solexa/Illumina short-read ultra-high throughput DNA sequencing technology produces millions of short tags (up to 36 bases) by parallel sequencing-by-synthesis of DNA colonies. The processing and statistical analysis of such high-throughput data poses new challenges; currently a fair proportion of the tags are routinely discarded due to an inability to match them to a reference sequence, thereby reducing the effective throughput of the technology. RESULTS: We propose a novel base calling algorithm using model-based clustering and probability theory to identify ambiguous bases and code them with IUPAC symbols. We also select optimal sub-tags using a score based on information content to remove uncertain bases towards the ends of the reads. CONCLUSION: We show that the method improves genome coverage and number of usable tags as compared with Solexa's data processing pipeline by an average of 15%. An R package is provided which allows fast and accurate base calling of Solexa's fluorescence intensity files and the production of informative diagnostic plots.

If reconfigurable processors are to become widely used, we will need tools to help conventional programmer use them. In particular, a single high-level language should be used to program the whole application; both the part which will become the hardware configuration and the part which remains software. Spyder is a reconfigurable processor with configurable execution units. The C++ language has been chosen as the source language to program this processor. In this paper we present a compiler capable of synthesizing the hardware configuration of FPGA execution units from C++ source code. The same source code can be compiled by a standard C++ compiler for simulation purposes. First estimates show that this approach leads to very short synthesize time as compared to VHDL synthesizer for a similar quality of the generated hardware.

A superscalar processor with three execution units is described in details in this paper. The execution units are implemented using reprogrammable field-programmable gate array (FPGA) chips, allowing the user to configure them to best fit the application. Each instruction, composed of 128 bits, directly controls all the processor resources, in a horizontal microprogramming way.>

Abstract The WORP project embodies the design of a real‐time oriented RISC microprocessor and a complete application development environment for this processor. The three most original aspects of this project are: (a) the microprocessor has no assembly language, but is programmed in microcode; the compiler will translate the high‐level language directly into microcode; (b) there is a certain amount of parallelism available at the microcode level; the compiler will take advantage of this parallelism without putting extra burden on the programmer; (c) the compiler performs instruction rescheduling in order to take further advantage of the parallelism available at the microcode level. This paper describes the high‐level language and compiler aspects of the WORP project, and concentrates on the instruction rescheduling and other optimizations performed by the compiler. A modest comparative bench‐mark is provided.