Artificial intelligence challenges in the face of biological threats: emerging catastrophic risks for public health.

The threat landscape of biological hazards with the evolution of AI presents challenges. While AI promises innovative solutions, concerns arise about its misuse in the creation of biological weapons. The convergence of AI and genetic editing raises questions about biosecurity, potentially accelerating the development of dangerous pathogens. The mapping conducted highlights the critical intersection between AI and biological threats, underscoring emerging risks in the criminal manipulation of pathogens. Technological advancement in biology requires preventative and regulatory measures. Expert recommendations emphasize the need for solid regulations and responsibility of creators, demanding a proactive, ethical approach and governance to ensure global safety.

Comparison of four DNA extraction methods for comprehensive assessment of 16S rRNA bacterial diversity in marine biofilms using high-throughput sequencing.

High-throughput DNA sequencing technologies are increasingly used for the metagenomic characterisation of microbial biodiversity. However, basic issues, such as the choice of an appropriate DNA extraction method, are still not resolved for non-model microbial communities. This study evaluates four commonly used DNA extraction methods for marine periphyton biofilms in terms of DNA yield, efficiency, purity, integrity and resulting 16S rRNA bacterial diversity. Among the tested methods, the Plant DNAzol® Reagent (PlantDNAzol) and the FastDNA® SPIN Kit for Soil (FastDNA Soil) methods were best suited to extract high quantities of DNA (77-130 µg g wet wt-1). Lower amounts of DNA were obtained (<37 µg g wet wt-1) with the Power Plant® Pro DNA Isolation Kit (PowerPlant) and the Power Biofilm® DNA Isolation Kit (PowerBiofilm) methods, but integrity and purity of the extracted DNA were higher. Results from 16S rRNA amplicon sequencing demonstrate that the choice of a DNA extraction method significantly influences the bacterial community profiles generated. A higher number of bacterial OTUs were detected when DNA was extracted with the PowerBiofilm and the PlantDNAzol methods. Overall, this study demonstrates the potential bias in metagenomic diversity estimates associated with different DNA extraction methods.

Seqenv: linking sequences to environments through text mining.

Understanding the distribution of taxa and associated traits across different environments is one of the central questions in microbial ecology. High-throughput sequencing (HTS) studies are presently generating huge volumes of data to address this biogeographical topic. However, these studies are often focused on specific environment types or processes leading to the production of individual, unconnected datasets. The large amounts of legacy sequence data with associated metadata that exist can be harnessed to better place the genetic information found in these surveys into a wider environmental context. Here we introduce a software program, seqenv, to carry out precisely such a task. It automatically performs similarity searches of short sequences against the "nt" nucleotide database provided by NCBI and, out of every hit, extracts-if it is available-the textual metadata field. After collecting all the isolation sources from all the search results, we run a text mining algorithm to identify and parse words that are associated with the Environmental Ontology (EnvO) controlled vocabulary. This, in turn, enables us to determine both in which environments individual sequences or taxa have previously been observed and, by weighted summation of those results, to summarize complete samples. We present two demonstrative applications of seqenv to a survey of ammonia oxidizing archaea as well as to a plankton paleome dataset from the Black Sea. These demonstrate the ability of the tool to reveal novel patterns in HTS and its utility in the fields of environmental source tracking, paleontology, and studies of microbial biogeography. To install seqenv, go to: https://github.com/xapple/seqenv.

Remnants of marine bacterial communities can be retrieved from deep sediments in lakes of marine origin.

Some bacteria can be preserved over time in deep sediments where they persist either in dormant or slow-growing vegetative stages. Here, we hypothesized that such cells can be revived when exposed to environmental conditions similar to those before they were buried in the sediments. To test this hypothesis, we collected bacteria from sediment samples of different ages (140-8500 calibrated years before present, cal BP) from three lakes that differed in the timing of their physical isolation from the Baltic Sea following postglacial uplift. After these bacterial communities were grown in sterile water from the Baltic Sea, we determined the proportion of 16S rRNA sequence reads associated with marine habitats by extracting the environment descriptive terms of homologous sequences retrieved from public databases. We found that the proportion of reads associated with marine descriptive term was significantly higher in cultures inoculated with sediment layers formed under Baltic conditions and where salinities were expected to be similar to current levels. Moreover, a similar pattern was found in the original sediment layers. Our study, therefore, suggests that remnants of marine bacterial communities can be preserved in sediments over thousands of years and can be revived from deep sediments in lakes of marine origin.

Tuning fresh: radiation through rewiring of central metabolism in streamlined bacteria.

Most free-living planktonic cells are streamlined and in spite of their limitations in functional flexibility, their vast populations have radiated into a wide range of aquatic habitats. Here we compared the metabolic potential of subgroups in the Alphaproteobacteria lineage SAR11 adapted to marine and freshwater habitats. Our results suggest that the successful leap from marine to freshwaters in SAR11 was accompanied by a loss of several carbon degradation pathways and a rewiring of the central metabolism. Examples for these are C1 and methylated compounds degradation pathways, the Entner-Doudouroff pathway, the glyoxylate shunt and anapleuretic carbon fixation being absent from the freshwater genomes. Evolutionary reconstructions further suggest that the metabolic modules making up these important freshwater metabolic traits were already present in the gene pool of ancestral marine SAR11 populations. The loss of the glyoxylate shunt had already occurred in the common ancestor of the freshwater subgroup and its closest marine relatives, suggesting that the adaptation to freshwater was a gradual process. Furthermore, our results indicate rapid evolution of TRAP transporters in the freshwater clade involved in the uptake of low molecular weight carboxylic acids. We propose that such gradual tuning of metabolic pathways and transporters toward locally available organic substrates is linked to the formation of subgroups within the SAR11 clade and that this process was critical for the freshwater clade to find and fix an adaptive phenotype.

Metagenomic insights into strategies of aerobic and anaerobic carbon and nitrogen transformation in boreal lakes.

Thousands of net-heterotrophic and strongly stratifying lakes dominate the boreal landscape. Besides their central role as emitters of greenhouse gases, we have only recently begun to understand the microbial systems driving the metabolic processes and elemental cycles in these lakes. Using shotgun metagenomics, we show that the functional potential differs among lake types, with humic lakes being particularly enriched in carbon degradation genes. Most of the metabolic pathways exhibit oxygen- and temperature-dependent stratification over depth, coinciding with shifts in bacterial community composition, implying that stratification is a major factor controlling lake metabolism. In the bottom waters, rare and poorly characterized taxa, such as ε-Proteobacteria, but also autotrophs, such as photolithotrophic Chlorobia were abundant. These oxygen-depleted layers exhibited high genetic potential for mineralization, but also for fixation of carbon and nitrogen, and genetic markers for both methane production and oxidation were present. Our study provides a first glimpse of the genetic versatility of freshwater anoxic zones, and demonstrates the potential for complete turnover of carbon compounds within the water column.

Bacterial diversity along a 2600 km river continuum.

The bacterioplankton diversity in large rivers has thus far been under-sampled despite the importance of streams and rivers as components of continental landscapes. Here, we present a comprehensive dataset detailing the bacterioplankton diversity along the midstream of the Danube River and its tributaries. Using 16S rRNA-gene amplicon sequencing, our analysis revealed that bacterial richness and evenness gradually declined downriver in both the free-living and particle-associated bacterial communities. These shifts were also supported by beta diversity analysis, where the effects of tributaries were negligible in regards to the overall variation. In addition, the river was largely dominated by bacteria that are commonly observed in freshwaters. Dominated by the acI lineage, the freshwater SAR11 (LD12) and the Polynucleobacter group, typical freshwater taxa increased in proportion downriver and were accompanied by a decrease in soil and groundwater-affiliated bacteria. Based on views of the meta-community and River Continuum Concept, we interpret the observed taxonomic patterns and accompanying changes in alpha and beta diversity with the intention of laying the foundation for a unified concept for river bacterioplankton diversity.

Microbial community composition and diversity via 16S rRNA gene amplicons: evaluating the illumina platform.

As new sequencing technologies become cheaper and older ones disappear, laboratories switch vendors and platforms. Validating the new setups is a crucial part of conducting rigorous scientific research. Here we report on the reliability and biases of performing bacterial 16S rRNA gene amplicon paired-end sequencing on the MiSeq Illumina platform. We designed a protocol using 50 barcode pairs to run samples in parallel and coded a pipeline to process the data. Sequencing the same sediment sample in 248 replicates as well as 70 samples from alkaline soda lakes, we evaluated the performance of the method with regards to estimates of alpha and beta diversity. Using different purification and DNA quantification procedures we always found up to 5-fold differences in the yield of sequences between individually barcodes samples. Using either a one-step or a two-step PCR preparation resulted in significantly different estimates in both alpha and beta diversity. Comparing with a previous method based on 454 pyrosequencing, we found that our Illumina protocol performed in a similar manner - with the exception for evenness estimates where correspondence between the methods was low. We further quantified the data loss at every processing step eventually accumulating to 50% of the raw reads. When evaluating different OTU clustering methods, we observed a stark contrast between the results of QIIME with default settings and the more recent UPARSE algorithm when it comes to the number of OTUs generated. Still, overall trends in alpha and beta diversity corresponded highly using both clustering methods. Our procedure performed well considering the precisions of alpha and beta diversity estimates, with insignificant effects of individual barcodes. Comparative analyses suggest that 454 and Illumina sequence data can be combined if the same PCR protocol and bioinformatic workflows are used for describing patterns in richness, beta-diversity and taxonomic composition.

HTSstation: a web application and open-access libraries for high-throughput sequencing data analysis.

The HTSstation analysis portal is a suite of simple web forms coupled to modular analysis pipelines for various applications of High-Throughput Sequencing including ChIP-seq, RNA-seq, 4C-seq and re-sequencing. HTSstation offers biologists the possibility to rapidly investigate their HTS data using an intuitive web application with heuristically pre-defined parameters. A number of open-source software components have been implemented and can be used to build, configure and run HTS analysis pipelines reactively. Besides, our programming framework empowers developers with the possibility to design their own workflows and integrate additional third-party software. The HTSstation web application is accessible at http://htsstation.epfl.ch.

PyroTRF-ID: a novel bioinformatics methodology for the affiliation of terminal-restriction fragments using 16S rRNA gene pyrosequencing data.

BACKGROUND: In molecular microbial ecology, massive sequencing is gradually replacing classical fingerprinting techniques such as terminal-restriction fragment length polymorphism (T-RFLP) combined with cloning-sequencing for the characterization of microbiomes. Here, a bioinformatics methodology for pyrosequencing-based T-RF identification (PyroTRF-ID) was developed to combine pyrosequencing and T-RFLP approaches for the description of microbial communities. The strength of this methodology relies on the identification of T-RFs by comparison of experimental and digital T-RFLP profiles obtained from the same samples. DNA extracts were subjected to amplification of the 16S rRNA gene pool, T-RFLP with the HaeIII restriction enzyme, 454 tag encoded FLX amplicon pyrosequencing, and PyroTRF-ID analysis. Digital T-RFLP profiles were generated from the denoised full pyrosequencing datasets, and the sequences contributing to each digital T-RF were classified to taxonomic bins using the Greengenes reference database. The method was tested both on bacterial communities found in chloroethene-contaminated groundwater samples and in aerobic granular sludge biofilms originating from wastewater treatment systems. RESULTS: PyroTRF-ID was efficient for high-throughput mapping and digital T-RFLP profiling of pyrosequencing datasets. After denoising, a dataset comprising ca. 10'000 reads of 300 to 500 bp was typically processed within ca. 20 minutes on a high-performance computing cluster, running on a Linux-related CentOS 5.5 operating system, enabling parallel processing of multiple samples. Both digital and experimental T-RFLP profiles were aligned with maximum cross-correlation coefficients of 0.71 and 0.92 for high- and low-complexity environments, respectively. On average, 63±18% of all experimental T-RFs (30 to 93 peaks per sample) were affiliated to phylotypes. CONCLUSIONS: PyroTRF-ID profits from complementary advantages of pyrosequencing and T-RFLP and is particularly adapted for optimizing laboratory and computational efforts to describe microbial communities and their dynamics in any biological system. The high resolution of the microbial community composition is provided by pyrosequencing, which can be performed on a restricted set of selected samples, whereas T-RFLP enables simultaneous fingerprinting of numerous samples at relatively low cost and is especially adapted for routine analysis and follow-up of microbial communities on the long run.