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A fundamental question in community ecology is the role of predator–prey interactions in food-web stability and species coexistence. Although microbial microcosms offer powerful systems to investigate it, interrogating the environment is much more arduous. Here, we show in a 1-year survey that the obligate predators Bdellovibrio and like organisms (BALOs) can regulate prey populations, possibly in a density-dependent manner, in the naturally complex, species-rich environments of wastewater treatment plants. Abundant as well as rarer prey populations are affected, leading to an oscillating predatory landscape shifting at various temporal scales in which the total population remains stable. Shifts, along with differential prey range, explain co-existence of the numerous predators through niche partitioning. We validate these sequence-based findings using single-cell sorting combined with fluorescent hybridization and community sequencing. Our approach should be applicable for deciphering community interactions in other systems. Studying the role of predator–prey interactions in food-web stability and species coexistence in the environment is arduous. Here, Cohen et al. use a combination of community and single-cell analyses to show that bacterial predators can regulate prey populations in the species-rich environments of wastewater treatment plants.

When reporting results of Gunshot Residue (GSR) analysis from a person suspected to be involved in a recent shooting, most forensic experts only provide the court with the raw results (i.e. the number of GSR particles found) and a disclaimer that a positive finding does not prove that the suspect was involved in a firearm shooting incident whilst a negative finding does not prove that he was not. Probabilistic analysis of the GSR results provides more value to the court, so the present study calculated likelihood ratio (LR) values for finding 0–8 characteristic GSR particles (containing Lead, Barium and Antimony) on a suspect's hands, based on the available GSR data from the published literature as well as studies by the authors. Defense propositions, i.e. modes for GSR acquisition other than involvement in a shooting event, were divided into three broad categories: low, medium and heavy background. For each background level and number of GSR particles found, minimal and maximal LR values were calculated. Thus, for each proposition the defense provides for the presence of GSR on the defendant's hands, the forensic expert can provide a possible set of minimal and maximal LR values, leaving the court to examine the defendant's contention and decide which of the three background modes is more plausible according to the circumstances of the specific case. •We calculate likelihood ratio values for finding characteristic GSR particles on a suspect.•Defense propositions are divided into three broad categories: low, medium and heavy background.•LR calculations are based on the available GSR data from published literature and studies.

Microbial communities in soils may change in accordance with distance, season, climate, soil texture and other environmental parameters. Microbial diversity patterns have been extensively surveyed in temperate regions, but few such studies attempted to address them with respect to spatial and temporal scales and their correlations to environmental factors, especially in arid ecosystems. In order to fill this gap on a regional scale, the molecular fingerprints and abundance of three taxonomic groups--Bacteria, α-Proteobacteria and Actinobacteria--were sampled from soils 0.5-100 km apart in arid, semi-arid, dry Mediterranean and shoreline Mediterranean regions in Israel. Additionally, on a local scale, the molecular fingerprints of three taxonomic groups--Bacteria, Archaea and Fungi--were sampled from soils 1 cm-500 m apart in the semi-arid region, in both summer and winter. Fingerprints of the Bacteria differentiated between all regions (P<0.02), while those of the α-Proteobacteria differentiated between some of the regions (0.010.05). Locally, fingerprints of archaea and fungi did not display distance-decay relationships (P>0.13), that is, the dissimilarity between communities did not increase with geographic distance. Neither was this phenomenon evident in bacterial samples in summer (P>0.24); in winter, however, differences between bacterial communities significantly increased as the geographic distances between them grew (P<0.01). Microbial community structures, as well as microbial abundance, were both significantly correlated to precipitation and soil characteristics: texture, organic matter and water content (R(2)>0.60, P<0.01). We conclude that on the whole, microbial biogeography in arid and semi-arid soils in Israel is determined more by specific environmental factors than geographic distances and spatial distribution patterns.

Predators feed on prey to acquire the nutrients necessary to sustain their survival, growth, and replication. InBdellovibrio bacteriovorus, an obligate predator of Gram-negative bacteria, cell growth and replication are tied to a shift from a motile, free-living phase of search and attack to a sessile, intracellular phase of growth and replication during which a single prey cell is consumed. Engagement and sustenance of growth are achieved through the sensing of two unidentified prey-derived cues. We developed a novel ex vivo cultivation system forB. bacteriovoruscomposed of prey ghost cells that are recognized and invaded by the predator. By manipulating their content, we demonstrated that an early cue is located in the prey envelope and a late cue is found within the prey soluble fraction. These spatially and temporally separated cues elicit discrete and combinatory regulatory effects on gene transcription. Together, they delimit a poorly characterized transitory phase between the attack phase and the growth phase, during which the bdelloplast (the invaded prey cell) is constructed. This transitory phase constitutes a checkpoint in which the late cue presumably acts as a determinant of the prey’s nutritional value before the predator commits. These regulatory adaptations to a unique bacterial lifestyle have not been reported previously.

The vast majority of known proteins have not been experimentally tested even at the level of measuring their expression, and the function of many proteins remains unknown. In order to decipher protein function and examine functional associations, we developed \"Cliquely\", a software tool based on the exploration of co-occurrence patterns. Using a set of more than 23 million proteins divided into 404,947 orthologous clusters, we explored the co-occurrence graph of 4,742 fully sequenced genomes from the three domains of life. Edge weights in this graph represent co-occurrence probabilities. We use the Bron-Kerbosch algorithm to detect maximal cliques in this graph, fully-connected subgraphs that represent meaningful biological networks from different functional categories. We demonstrate that Cliquely can successfully identify known networks from various pathways, including nitrogen fixation, glycolysis, methanogenesis, mevalonate and ribosome proteins. Identifying the virulence-associated type III secretion system (T3SS) network, Cliquely also added 13 previously uncharacterized novel proteins to the T3SS network, demonstrating the strength of this approach. Cliquely is freely available and open source. Users can employ the tool to explore co-occurrence networks using a protein of interest and a customizable level of stringency, either for the entire dataset or for a one of the three domains-Archaea, Bacteria, or Eukarya.

Post-partum metritis is among the most prevalent disease in dairy cows affecting animal welfare and inflicting considerable economic loses. While post-partum contamination of the uterus is rife in dairy cows, only a fraction of these animals will develop metritis. Our main objective was to compare the bacterial communities and the inflammatory response in the endometrium of healthy and metritic dairy cows. Holstein–Friesian cows ( n  = 35) were sampled immediately following clinical classification as healthy ( n  = 21), suffering from metritis ( n  = 13) or septic metritis ( n  = 1), based on veterinary examination at 5–10 days post-partum. Polymorphonuclear cells (PMN) percentage in endometrial cytology was significantly higher in cows with metritis. Full-thickness uterine biopsy analysis revealed that the luminal epithelium in inter-caruncle areas was preserved in healthy cows, but in metritis it was compromised, with marked PMN infiltration particularly in the apical endometrium. Gram staining revealed that bacterial load and spatial distribution was associated with disease severity. 16S-rDNA bacterial community analysis revealed unique endometrial bacterial community composition in metritic cows, as compared to more diverse communities among healthy cows. The most abundant phyla in healthy cows were Proteobacteria (31.8 ± 9.3%), Firmicutes (27.9 ± 8.4%) and Bacteroidetes (19.7 ± 7.2%), while Bacteroidetes (60.3 ± 10.3%), Fusobacteria (13.4 ± 5.9%) and Firmicutes (10.5 ± 3.3%) were most abundant in the endometrial mucosa of metritic cows. Relative abundance of Bacteroidetes (19.7 ± 7.2% vs. 60.3 ± 10.3%), Fusobacteria (7.5 ± 5.2% vs. 13.4 ± 5.9%) and Proteobacteria (31.8 ± 9.3% vs. 7.3 ± 5.6%) phyla differed significantly between healthy and metritic cows. In summary, endometrial PMN abundance, spatial distribution and bacterial communities differed between healthy and metritic dairy cows at early post-partum.

Finding optimal markers for microorganisms important in the medical, agricultural, environmental or ecological fields is of great importance. Thousands of complete microbial genomes now available allow us, for the first time, to exhaustively identify marker proteins for groups of microbial organisms. In this work, we model the biological task as the well-known mathematical \"hitting set\" problem, solving it based on both greedy and randomized approximation algorithms. We identify unique markers for 17 phenotypic and taxonomic microbial groups, including proteins related to the nitrite reductase enzyme as markers for the non-anammox nitrifying bacteria group, and two transcription regulation proteins, nusG and yhiF, as markers for the Archaea and Escherichia/Shigella taxonomic groups, respectively. Additionally, we identify marker proteins for three subtypes of pathogenic E. coli, which previously had no known optimal markers. Practically, depending on the completeness of the database this algorithm can be used for identification of marker genes for any microbial group, these marker genes may be prime candidates for the understanding of the genetic basis of the group's phenotype or to help discover novel functions which are uniquely shared among a group of microbes. We show that our method is both theoretically and practically efficient, while establishing an upper bound on its time complexity and approximation ratio; thus, it promises to remain efficient and permit the identification of marker proteins that are specific to phenotypic or taxonomic groups, even as more and more bacterial genomes are being sequenced.

On dairy farms in hot climates worldwide, cows suffer from heat stress, which is alleviated by the use of water cooling systems. Sprinklers and showerheads are known to support the development of microbial biofilms, which can be a source of infection by pathogenic microorganisms. The aim of this study was to investigate the presence of microbial biofilms in dairy cooling systems, and to analyze their population compositions using culture-independent technique, 16S rRNA gene sequencing. Biofilm samples were collected on eight dairy farms from 40 sprinklers and the microbial constituents were identified by deep sequencing of the 16S rRNA gene. A total of 9,374 operational taxonomic units (OTUs) was obtained from all samples. The mean richness of the samples was 465 ± 268 OTUs which were classified into 26 different phyla; 76% of the reads belonged to only three phyla: Proteobacteria, Actinobacteria and Firmicutes. Although the most prevalent OTUs (Paracoccus, Methyloversatilis, Brevundimonas, Porphyrobacter, Gp4, Mycobacterium, Hyphomicrobium, Corynebacterium and Clostridium) were shared by all farms, each farm formed a unique microbial pattern. Some known potential human and livestock pathogens were found to be closely related to the OTUs found in this study. This work demonstrates the presence of biofilm in dairy cooling systems which may potentially serve as a live source for microbial pathogens.

ABSTRACT Forensics aims at using physical evidence to solve investigations with science-based principles, thus operating within a theoretical framework. This however is often rather weak, the exception being DNA-based human forensics that is well anchored in theory. Soil is a most commonly encountered, easily and unknowingly transferred evidence but it is seldom employed as soil analyses require extensive expertise. In contrast, comparative analyses of soil bacterial communities using nucleic acid technologies can efficiently and precisely locate the origin of forensic soil traces. However, this application is still in its infancy, and is very rarely used. We posit that understanding the theoretical bases and limitations of their uses is essential for soil microbial forensics to be judiciously implemented. Accordingly, we review the ecological theory and experimental evidence explaining differences between soil microbial communities, i.e. the generation of beta diversity, and propose to integrate a bottom-up approach of interactions at the microscale, reflecting historical contingencies with top-down mechanisms driven by the geographic template, providing a potential explanation as to why bacterial communities map according to soil types. Finally, we delimit the use of soil microbial forensics based on the present technologies and ecological knowledge, and propose possible venues to remove existing bottlenecks. The authors describe the application and current limitations of molecular microbial ecology to soil forensics, and provide the ecological theory background on which the approach relies, linking microscale and macroscale processes.

Predatory bacteria seek and consume other live bacteria. Although belonging to taxonomically diverse groups, relatively few bacterial predator species are known. Consequently, it is difficult to assess the impact of predation within the bacterial realm. As no genetic signatures distinguishing them from non-predatory bacteria are known, genomic resources cannot be exploited to uncover novel predators. In order to identify genes specific to predatory bacteria, we developed a bioinformatic tool called DiffGene. This tool automatically identifies marker genes that are specific to phenotypic or taxonomic groups, by mapping the complete gene content of all available fully-sequenced genomes for the presence/absence of each gene in each genome. A putative 'predator region' of ~60 amino acids in the tryptophan 2,3-dioxygenase (TDO) protein was found to probably be a predator-specific marker. This region is found in all known obligate predator and a few facultative predator genomes, and is absent from most facultative predators and all non-predatory bacteria. We designed PCR primers that uniquely amplify a ~180bp-long sequence within the predators' TDO gene, and validated them in monocultures as well as in metagenetic analysis of environmental wastewater samples. This marker, in addition to its usage in predator identification and phylogenetics, may finally permit reliable enumeration and cataloguing of predatory bacteria from environmental samples, as well as uncovering novel predators.