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\"Bioremediation using microbes is a sustainable technology for biodegradation of target compounds and OMICS approach gives more clarity on these microbial communities. This book provides insights into the complex behavior of microbial communities and identifies enzymes/metabolites and their degradation pathways. It describes the application of microbes and their derivatives for bioremediation of potentially toxic and novel compounds. It highlights existing technologies along with industrial practices and real-life case studies. Features: Includes recent research and development in the areas of OMICS and microbial bioremediation. Covers the broad environmental pollution control approach such as metagenomics, metabolomics, fluxomics, bioremediation, and biodegradation of industrial wastes. Reviews metagenomics and waste management, and recycling for environmental cleanup. Describes the metagenomic methodologies and best practices, from sample collection to data analysis for taxonomies. Explores various microbial degradation pathways and detoxification mechanisms for organic and inorganic contaminants of wastewater with their gene expression. This book aims at Graduate students and researchers in environmental engineering, soil remediation, hazardous waste management, environmental modeling, and wastewater treatment\"-- Provided by publisher.

Mutation is the engine that drives evolution and adaptation forward in that it generates the variation on which natural selection acts. Mutation is a random process that nevertheless occurs according to certain biases. Elucidating mutational biases and the way they vary across species and within genomes is crucial to understanding evolution and adaptation. Here we demonstrate that clonal pathogens that evolve under severely relaxed selection are uniquely suitable for studying mutational biases in bacteria. We estimate mutational patterns using sequence datasets from five such clonal pathogens belonging to four diverse bacterial clades that span most of the range of genomic nucleotide content. We demonstrate that across different types of sites and in all four clades mutation is consistently biased towards AT. This is true even in clades that have high genomic GC content. In all studied cases the mutational bias towards AT is primarily due to the high rate of C/G to T/A transitions. These results suggest that bacterial mutational biases are far less variable than previously thought. They further demonstrate that variation in nucleotide content cannot stem entirely from variation in mutational biases and that natural selection and/or a natural selection-like process such as biased gene conversion strongly affect nucleotide content.

, a coastal marine bacterium and opportunistic pathogen, poses increasing health risks due to rising sea water temperatures. While it harbors diverse virulence factors, its disease mechanisms remain poorly understood. To address this, we sequenced 82 environmental isolates from the Baltic Sea and combined them with 325 published genomes (clinical and environmental) for comparative analysis. Phylogenetic reconstruction revealed four major lineages, with Baltic strains restricted to L2 and L4. Clinical and environmental strains were found across all lineages, suggesting phylogeny reflects environmental adaptation more than pathogenicity. Using our newly developed PhyloBOTL pipeline, we identified 128 orthologs enriched in clinical isolates, grouped into 36 co-localization clusters. These include both known and novel virulence candidates, such as chaperone-usher pili, type VI secretion effectors, and spermidine synthases. Some clusters showed convergent loss across clades, implying niche-specific evolution. We also designed PCR primers targeting these genes to aid in the surveillance of pathogenic strains.IMPORTANCE is a naturally occurring marine bacterium that can cause life-threatening infections, with incidence increasing as coastal waters warm due to climate change. Determining which environmental strains pose the greatest risk remains a major challenge for public health surveillance. By analyzing hundreds of genomes from globally distributed strains, including extensive sampling from the rapidly warming Baltic Sea, this study shows that pathogenic potential is not restricted to specific evolutionary lineages but is instead associated with distinct sets of genes enriched in clinical strains. To support pathogen detection, we developed PCR primers targeting a subset of these clinically associated genes. Together, these findings provide new insight into the molecular basis of infections and offer practical tools for improved detection, monitoring, and risk assessment of harmful strains in coastal waters and seafood under ongoing climate change.

Recent research has provided mechanistic insight into the important contributions of the gut microbiota to vertebrate biology, but questions remain about the evolutionary processes that have shaped this symbiosis. In the present study, we showed in experiments with gnotobiotic mice that the evolution of Lactobacillus reuteri with rodents resulted in the emergence of host specialization. To identify genomic events marking adaptations to the murine host, we compared the genome of the rodent isolate L. reuteri 100-23 with that of the human isolate L. reuteri F275, and we identified hundreds of genes that were specific to each strain. In order to differentiate true host-specific genome content from strain-level differences, comparative genome hybridizations were performed to query 57 L. reuteri strains originating from six different vertebrate hosts in combination with genome sequence comparisons of nine strains encompassing five phylogenetic lineages of the species. This approach revealed that rodent strains, although showing a high degree of genomic plasticity, possessed a specific genome inventory that was rare or absent in strains from other vertebrate hosts. The distinct genome content of L. reuteri lineages reflected the niche characteristics in the gastrointestinal tracts of their respective hosts, and inactivation of seven out of eight representative rodent-specific genes in L. reuteri 100-23 resulted in impaired ecological performance in the gut of mice. The comparative genomic analyses suggested fundamentally different trends of genome evolution in rodent and human L. reuteri populations, with the former possessing a large and adaptable pan-genome while the latter being subjected to a process of reductive evolution. In conclusion, this study provided experimental evidence and a molecular basis for the evolution of host specificity in a vertebrate gut symbiont, and it identified genomic events that have shaped this process.

Microbial minimal generation times range from a few minutes to several weeks. They are evolutionarily determined by variables such as environment stability, nutrient availability, and community diversity. Selection for fast growth adaptively imprints genomes, resulting in gene amplification, adapted chromosomal organization, and biased codon usage. We found that these growth-related traits in 214 species of bacteria and archaea are highly correlated, suggesting they all result from growth optimization. While modeling their association with maximal growth rates in view of synthetic biology applications, we observed that codon usage biases are better correlates of growth rates than any other trait, including rRNA copy number. Systematic deviations to our model reveal two distinct evolutionary processes. First, genome organization shows more evolutionary inertia than growth rates. This results in over-representation of growth-related traits in fast degrading genomes. Second, selection for these traits depends on optimal growth temperature: for similar generation times purifying selection is stronger in psychrophiles, intermediate in mesophiles, and lower in thermophiles. Using this information, we created a predictor of maximal growth rate adapted to small genome fragments. We applied it to three metagenomic environmental samples to show that a transiently rich environment, as the human gut, selects for fast-growers, that a toxic environment, as the acid mine biofilm, selects for low growth rates, whereas a diverse environment, like the soil, shows all ranges of growth rates. We also demonstrate that microbial colonizers of babies gut grow faster than stabilized human adults gut communities. In conclusion, we show that one can predict maximal growth rates from sequence data alone, and we propose that such information can be used to facilitate the manipulation of generation times. Our predictor allows inferring growth rates in the vast majority of uncultivable prokaryotes and paves the way to the understanding of community dynamics from metagenomic data.

Herbivores can gain indirect access to recalcitrant carbon present in plant cell walls through symbiotic associations with lignocellulolytic microbes. A paradigmatic example is the leaf-cutter ant (Tribe: Attini), which uses fresh leaves to cultivate a fungus for food in specialized gardens. Using a combination of sugar composition analyses, metagenomics, and whole-genome sequencing, we reveal that the fungus garden microbiome of leaf-cutter ants is composed of a diverse community of bacteria with high plant biomass-degrading capacity. Comparison of this microbiome's predicted carbohydrate-degrading enzyme profile with other metagenomes shows closest similarity to the bovine rumen, indicating evolutionary convergence of plant biomass degrading potential between two important herbivorous animals. Genomic and physiological characterization of two dominant bacteria in the fungus garden microbiome provides evidence of their capacity to degrade cellulose. Given the recent interest in cellulosic biofuels, understanding how large-scale and rapid plant biomass degradation occurs in a highly evolved insect herbivore is of particular relevance for bioenergy.

Metarhizium spp. are being used as environmentally friendly alternatives to chemical insecticides, as model systems for studying insect-fungus interactions, and as a resource of genes for biotechnology. We present a comparative analysis of the genome sequences of the broad-spectrum insect pathogen Metarhizium anisopliae and the acridid-specific M. acridum. Whole-genome analyses indicate that the genome structures of these two species are highly syntenic and suggest that the genus Metarhizium evolved from plant endophytes or pathogens. Both M. anisopliae and M. acridum have a strikingly larger proportion of genes encoding secreted proteins than other fungi, while ~30% of these have no functionally characterized homologs, suggesting hitherto unsuspected interactions between fungal pathogens and insects. The analysis of transposase genes provided evidence of repeat-induced point mutations occurring in M. acridum but not in M. anisopliae. With the help of pathogen-host interaction gene database, ~16% of Metarhizium genes were identified that are similar to experimentally verified genes involved in pathogenicity in other fungi, particularly plant pathogens. However, relative to M. acridum, M. anisopliae has evolved with many expanded gene families of proteases, chitinases, cytochrome P450s, polyketide synthases, and nonribosomal peptide synthetases for cuticle-degradation, detoxification, and toxin biosynthesis that may facilitate its ability to adapt to heterogeneous environments. Transcriptional analysis of both fungi during early infection processes provided further insights into the genes and pathways involved in infectivity and specificity. Of particular note, M. acridum transcribed distinct G-protein coupled receptors on cuticles from locusts (the natural hosts) and cockroaches, whereas M. anisopliae transcribed the same receptor on both hosts. This study will facilitate the identification of virulence genes and the development of improved biocontrol strains with customized properties.

Massively parallel pyrosequencing of hypervariable regions from small subunit ribosomal RNA (SSU rRNA) genes can sample a microbial community two or three orders of magnitude more deeply per dollar and per hour than capillary sequencing of full-length SSU rRNA. As with full-length rRNA surveys, each sequence read is a tag surrogate for a single microbe. However, rather than assigning taxonomy by creating gene trees de novo that include all experimental sequences and certain reference taxa, we compare the hypervariable region tags to an extensive database of rRNA sequences and assign taxonomy based on the best match in a Global Alignment for Sequence Taxonomy (GAST) process. The resulting taxonomic census provides information on both composition and diversity of the microbial community. To determine the effectiveness of using only hypervariable region tags for assessing microbial community membership, we compared the taxonomy assigned to the V3 and V6 hypervariable regions with the taxonomy assigned to full-length SSU rRNA sequences isolated from both the human gut and a deep-sea hydrothermal vent. The hypervariable region tags and full-length rRNA sequences provided equivalent taxonomy and measures of relative abundance of microbial communities, even for tags up to 15% divergent from their nearest reference match. The greater sampling depth per dollar afforded by massively parallel pyrosequencing reveals many more members of the \"rare biosphere\" than does capillary sequencing of the full-length gene. In addition, tag sequencing eliminates cloning bias and the sequences are short enough to be completely sequenced in a single read, maximizing the number of organisms sampled in a run while minimizing chimera formation. This technique allows the cost-effective exploration of changes in microbial community structure, including the rare biosphere, over space and time and can be applied immediately to initiatives, such as the Human Microbiome Project.

The experimental evolution of laboratory populations of microbes provides an opportunity to observe the evolutionary dynamics of adaptation in real time. Until very recently, however, such studies have been limited by our inability to systematically find mutations in evolved organisms. We overcome this limitation by using a variety of DNA microarray-based techniques to characterize genetic changes -- including point mutations, structural changes, and insertion variation -- that resulted from the experimental adaptation of 24 haploid and diploid cultures of Saccharomyces cerevisiae to growth in either glucose, sulfate, or phosphate-limited chemostats for approximately 200 generations. We identified frequent genomic amplifications and rearrangements as well as novel retrotransposition events associated with adaptation. Global nucleotide variation detection in ten clonal isolates identified 32 point mutations. On the basis of mutation frequencies, we infer that these mutations and the subsequent dynamics of adaptation are determined by the batch phase of growth prior to initiation of the continuous phase in the chemostat. We relate these genotypic changes to phenotypic outcomes, namely global patterns of gene expression, and to increases in fitness by 5-50%. We found that the spectrum of available mutations in glucose- or phosphate-limited environments combined with the batch phase population dynamics early in our experiments allowed several distinct genotypic and phenotypic evolutionary pathways in response to these nutrient limitations. By contrast, sulfate-limited populations were much more constrained in both genotypic and phenotypic outcomes. Thus, the reproducibility of evolution varies with specific selective pressures, reflecting the constraints inherent in the system-level organization of metabolic processes in the cell. We were able to relate some of the observed adaptive mutations (e.g., transporter gene amplifications) to known features of the relevant metabolic pathways, but many of the mutations pointed to genes not previously associated with the relevant physiology. Thus, in addition to answering basic mechanistic questions about evolutionary mechanisms, our work suggests that experimental evolution can also shed light on the function and regulation of individual metabolic pathways.

The genomic GC-content of bacteria varies dramatically, from less than 20% to more than 70%. This variation is generally ascribed to differences in the pattern of mutation between bacteria. Here we test this hypothesis by examining patterns of synonymous polymorphism using datasets from 149 bacterial species. We find a large excess of synonymous GC→AT mutations over AT→GC mutations segregating in all but the most AT-rich bacteria, across a broad range of phylogenetically diverse species. We show that the excess of GC→AT mutations is inconsistent with mutation bias, since it would imply that most GC-rich bacteria are declining in GC-content; such a pattern would be unsustainable. We also show that the patterns are probably not due to translational selection or biased gene conversion, because optimal codons tend to be AT-rich, and the excess of GC→AT SNPs is observed in datasets with no evidence of recombination. We therefore conclude that there is selection to increase synonymous GC-content in many species. Since synonymous GC-content is highly correlated to genomic GC-content, we further conclude that there is selection on genomic base composition in many bacteria.