Microbial Genomes Research Articles

Bovine milk osteopontin improved intestinal health of pregnant rats fed a high-fat diet through improving bile acid metabolism

The main purpose of the current study was to investigate the ameliorative effects of bovine milk osteopontin (bmOPN) on the gut dysfunction of pregnant rats fed a high-fat diet (HFD). Bovine milk osteopontin was supplemented at a dose of 6 mg/kg body weight. Bovine milk osteopontin supplementation during pregnancy reduced colonic inflammation of HFD dams, and it also increased the colonic expression of ZO-1 and claudin-4 of HFD dams. Bovine milk osteopontin significantly enriched the relative abundance of Bacteroidetes, whereas it decreased Proteobacteria, Helicobacteraceae, and Desulfovibrionaceae in feces of HFD dams. The levels of isobutyric acid and pentanoic acid in the HFD + bmOPN group were higher than that of the HFD group. Functional predication analysis of microbial genomes revealed that bmOPN supplementation to HFD pregnancies changed 4 Kyoto Encyclopedia of Genes and Genomes pathways including bile acid biosynthesis. Further, bmOPN enriched hepatic taurochenodeoxycholic acid and tauroursodeoxycholic acid plus taurohyodeoxycholic acid in the gut of HFD maternal rats. Our findings suggested that bmOPN improved the gut health of HFD pregnant rats partially through modulating bile acid biosynthesis.

Biochar as an Environment-Friendly Alternative for Multiple Applications

The climate crisis and years of unsustainable agricultural practices have reduced soil fertility and crop yield. In addition, agricultural lands contribute more than 10% of greenhouse gases (GHGs). These concerns can be addressed by using biochar for carbon neutralization, environmental restoration, and agricultural management. Biochar has a role in nitrous oxide and methane gas emission mitigation from agricultural soil. New methods are needed to link belowground processes to functioning in multi-species and multi-cultivar agroecosystems. The intricate relationship between biochar and the composition of soil microbial communities, along with its impacts on functions within the rhizosphere, constitutes a highly perplexing and elusive subject within microbial genomics. The present review discusses how biochar can mitigate climate change, enhance carbon sequestration, and support crop productivity. Biochar could be a potential solution to mitigate soil microplastics and heavy metal contamination. Applying a biochar-based microbiome reduces polycyclic aromatic hydrocarbons (PAHs) in soil. The current knowledge and perspectives on biochar–plant–microbial interactions for sustainable agriculture and ameliorating the adverse effects of climate change are highlighted. In this review, a holistic approach was used to emphasize the utility of biochar for multiple applications with positive and negative effects and its role in promoting a functional circular economy.

Robotic workflows for automated long-term adaptive laboratory evolution: improving ethanol utilization by Corynebacterium glutamicum

BackgroundAdaptive laboratory evolution (ALE) is known as a powerful tool for untargeted engineering of microbial strains and genomics research. It is particularly well suited for the adaptation of microorganisms to new environmental conditions, such as alternative substrate sources. Since the probability of generating beneficial mutations increases with the frequency of DNA replication, ALE experiments are ideally free of constraints on the required duration of cell proliferation.ResultsHere, we present an extended robotic workflow for performing long-term evolution experiments based on fully automated repetitive batch cultures (rbALE) in a well-controlled microbioreactor environment. Using a microtiter plate recycling approach, the number of batches and thus cell generations is technically unlimited. By applying the validated workflow in three parallel rbALE runs, ethanol utilization by Corynebacterium glutamicum ATCC 13032 (WT) was significantly improved. The evolved mutant strain WT_EtOH-Evo showed a specific ethanol uptake rate of 8.45 ± 0.12 mmolEtOH gCDW−1 h−1 and a growth rate of 0.15 ± 0.01 h−1 in lab-scale bioreactors. Genome sequencing of this strain revealed a striking single nucleotide variation (SNV) upstream of the ald gene (NCgl2698, cg3096) encoding acetaldehyde dehydrogenase (ALDH). The mutated basepair was previously predicted to be part of the binding site for the global transcriptional regulator GlxR, and re-engineering demonstrated that the identified SNV is key for enhanced ethanol assimilation. Decreased binding of GlxR leads to increased synthesis of the rate-limiting enzyme ALDH, which was confirmed by proteomics measurements.ConclusionsThe established rbALE technology is generally applicable to any microbial strain and selection pressure that fits the small-scale cultivation format. In addition, our specific results will enable improved production processes with C. glutamicum from ethanol, which is of particular interest for acetyl-CoA-derived products.

Ancient Clostridium DNA and variants of tetanus neurotoxins associated with human archaeological remains

The analysis of microbial genomes from human archaeological samples offers a historic snapshot of ancient pathogens and provides insights into the origins of modern infectious diseases. Here, we analyze metagenomic datasets from 38 human archaeological samples and identify bacterial genomic sequences related to modern-day Clostridium tetani, which produces the tetanus neurotoxin (TeNT) and causes the disease tetanus. These genomic assemblies had varying levels of completeness, and a subset of them displayed hallmarks of ancient DNA damage. Phylogenetic analyses revealed known C. tetani clades as well as potentially new Clostridium lineages closely related to C. tetani. The genomic assemblies encode 13 TeNT variants with unique substitution profiles, including a subgroup of TeNT variants found exclusively in ancient samples from South America. We experimentally tested a TeNT variant selected from an ancient Chilean mummy sample and found that it induced tetanus muscle paralysis in mice, with potency comparable to modern TeNT. Thus, our ancient DNA analysis identifies DNA from neurotoxigenic C. tetani in archaeological human samples, and a novel variant of TeNT that can cause disease in mammals.

Removal of false positives in metagenomics-based taxonomy profiling via targeting Type IIB restriction sites

Accurate species identification and abundance estimation are critical for the interpretation of whole metagenome sequencing (WMS) data. Yet, existing metagenomic profilers suffer from false-positive identifications, which can account for more than 90% of total identified species. Here, by leveraging species-specific Type IIB restriction endonuclease digestion sites as reference instead of universal markers or whole microbial genomes, we present a metagenomic profiler, MAP2B (MetAgenomic Profiler based on type IIB restriction sites), to resolve those issues. We first illustrate the pitfalls of using relative abundance as the only feature in determining false positives. We then propose a feature set to distinguish false positives from true positives, and using simulated metagenomes from CAMI2, we establish a false-positive recognition model. By benchmarking the performance in metagenomic profiling using a simulation dataset with varying sequencing depth and species richness, we illustrate the superior performance of MAP2B over existing metagenomic profilers in species identification. We further test the performance of MAP2B using real WMS data from an ATCC mock community, confirming its superior precision against sequencing depth. Finally, by leveraging WMS data from an IBD cohort, we demonstrate the taxonomic features generated by MAP2B can better discriminate IBD and predict metabolomic profiles.

A bioinformatic workflow for in silico secretome prediction with the lignocellulose degrading ascomycete fungus Parascedosporium putredinis NO1.

The increasing availability of microbial genome sequences provides a reservoir of information for the identification of new microbial enzymes. Genes encoding proteins engaged in extracellular processes are of particular interest as these mediate the interactions microbes have with their environments. However, proteomic analysis of secretomes is challenging and often captures intracellular proteins released through cell death and lysis. Secretome prediction workflows from sequence data are commonly used to filter proteins identified through proteomics but are often simplified to a single step and are not evaluated bioinformatically for their effectiveness. Here, a workflow to predict a fungal secretome was designed and applied to the coding regions of the Parascedosporium putredinis NO1 genome. This ascomycete fungus is an exceptional lignocellulose degrader from which a new lignin-degrading enzyme has previously been identified. The 'secretome isolation' workflow is based on two strategies of localisation prediction and secretion prediction each utilising multiple available tools. The workflow produced three final secretomes with increasing levels of stringency. All three secretomes showed increases in functional annotations for extracellular processes and reductions in annotations for intracellular processes. Multiple sequences isolated as part of the secretome lacked any functional annotation and made exciting candidates for novel enzyme discovery.

Microbial siderophores as molecular shuttles for metal cations: sources, sinks and application perspectives.

Iron is one of the highly abundant elements on the earth's crust, an essential micronutrient for a majority of life forms, and exists in two frequent oxidation states such as ferrous (Fe2+) and ferric (Fe3+). These two oxidation states are interconvertible by redox reactions and form complexes with a wide range of siderophores. At neutral pH in soil, Fe2+ is highly soluble upto 100mM but have less biological value, whereas Fe3+ is less soluble upto 10-9M. This reduced bioavailability of Fe3+ induces competition among microorganisms. As many microorganisms need at least 10-6M of Fe3+ form of iron for their growth, siderophores from these microbes readily withdraw Fe3+ iron from a variety of habitats for their survival. In this review, we bring into light the several recent investigations related to diverse chemistry of microbial siderophores, mechanisms of siderophore uptake, biosynthetic gene clusters in microbial genomes, various sources of heavy metal cations in soil, siderophore-binding protein receptors and commercialisation perspectives of siderophores. Besides, this review unearths the recent advancements in the characterisation of novel siderophores and its heavy metal complexes alongside the interaction kinetics with receptors.

Flux balance analysis-based metabolic modeling of microbial secondary metabolism: Current status and outlook.

In microorganisms, different from primary metabolism for cellular growth, secondary metabolism is for ecological interactions and stress responses and an important source of natural products widely used in various areas such as pharmaceutics and food additives. With advancements of sequencing technologies and bioinformatics tools, a large number of biosynthetic gene clusters of secondary metabolites have been discovered from microbial genomes. However, due to challenges from the difficulty of genome-scale pathway reconstruction and the limitation of conventional flux balance analysis (FBA) on secondary metabolism, the quantitative modeling of secondary metabolism is poorly established, in contrast to that of primary metabolism. This review first discusses current efforts on the reconstruction of secondary metabolic pathways in genome-scale metabolic models (GSMMs), as well as related FBA-based modeling techniques. Additionally, potential extensions of FBA are suggested to improve the prediction accuracy of secondary metabolite production. As this review posits, biosynthetic pathway reconstruction for various secondary metabolites will become automated and a modeling framework capturing secondary metabolism onset will enhance the predictive power. Expectedly, an improved FBA-based modeling workflow will facilitate quantitative study of secondary metabolism and in silico design of engineering strategies for natural product production.

Growth-dependent Gene Expression Variation Influences the Strength of Codon Usage Biases.

The most highly expressed genes in microbial genomes tend to use a limited set of synonymous codons, often referred to as "preferred codons." The existence of preferred codons is commonly attributed to selection pressures on various aspects of protein translation including accuracy and/or speed. However, gene expression is condition-dependent and even within single-celled organisms transcript and protein abundances can vary depending on a variety of environmental and other factors. Here, we show that growth rate-dependent expression variation is an important constraint that significantly influences the evolution of gene sequences. Using large-scale transcriptomic and proteomic data sets in Escherichia coli and Saccharomyces cerevisiae, we confirm that codon usage biases are strongly associated with gene expression but highlight that this relationship is most pronounced when gene expression measurements are taken during rapid growth conditions. Specifically, genes whose relative expression increases during periods of rapid growth have stronger codon usage biases than comparably expressed genes whose expression decreases during rapid growth conditions. These findings highlight that gene expression measured in any particular condition tells only part of the story regarding the forces shaping the evolution of microbial gene sequences. More generally, our results imply that microbial physiology during rapid growth is critical for explaining long-term translational constraints.

IDeLUCS: a deep learning interactive tool for alignment-free clustering of DNA sequences.

We present an interactive Deep Learning-based software tool for Unsupervised Clustering of DNA Sequences (iDeLUCS), that detects genomic signatures and uses them to cluster DNA sequences, without the need for sequence alignment or taxonomic identifiers. iDeLUCS is scalable and user-friendly: its graphical user interface, with support for hardware acceleration, allows the practitioner to fine-tune the different hyper-parameters involved in the training process without requiring extensive knowledge of deep learning. The performance of iDeLUCS was evaluated on a diverse set of datasets: several real genomic datasets from organisms in kingdoms Animalia, Protista, Fungi, Bacteria, and Archaea, three datasets of viral genomes, a dataset of simulated metagenomic reads from microbial genomes, and multiple datasets of synthetic DNA sequences. The performance of iDeLUCS was compared to that of two classical clustering algorithms (k-means++ and GMM) and two clustering algorithms specialized in DNA sequences (MeShClust v3.0 and DeLUCS), using both intrinsic cluster evaluation metrics and external evaluation metrics. In terms of unsupervised clustering accuracy, iDeLUCS outperforms the two classical algorithms by an average of ∼20%, and the two specialized algorithms by an average of ∼12%, on the datasets of real DNA sequences analyzed. Overall, our results indicate that iDeLUCS is a robust clustering method suitable for the clustering of large and diverse datasets of unlabeled DNA sequences. iDeLUCS is available at https://github.com/Kari-Genomics-Lab/iDeLUCS under the terms of the MIT licence.

Metagenomic analysis of soybean endosphere microbiome to reveal signatures of microbes for health and disease

BackgroundSoil metagenomics is a cultivation-independent molecular strategy for investigating and exploiting the diversity of soil microbial communities. Soil microbial diversity is essential because it is critical to sustaining soil health for agricultural productivity and protection against harmful organisms. This study aimed to perform a metagenomic analysis of the soybean endosphere (all microbial communities found in plant leaves) to reveal signatures of microbes for health and disease. ResultsThe dataset is based on the National Center for Biotechnology Information (NCBI) Sequence Read Archive (SRA) release “microbial diversity in soybean”. The quality control process rejected 21 of the evaluated sequences (0.03% of the total sequences). Dereplication determined that 68,994 sequences were artificial duplicate readings, and removed them from consideration. Ribosomal Ribonucleic acid (RNA) genes were present in 72,747 sequences that successfully passed quality control (QC). Finally, we found that hierarchical classification for taxonomic assignment was conducted using MG-RAST, and the considered dataset of the metagenome domain of bacteria (99.68%) dominated the other groups. In Eukaryotes (0.31%) and unclassified sequence 2 (0.00%) in the taxonomic classification of bacteria in the genus group, Streptomyces, Chryseobacterium, Ppaenibacillus, Bacillus, and Mitsuaria were found. We also found some biological pathways, such as CMP-KDO biosynthesis II (from D-arabinose 5-phosphate), tricarboxylic acid cycle (TCA) cycle (plant), citrate cycle (TCA cycle), fatty acid biosynthesis, and glyoxylate and dicarboxylate metabolism. Gene prediction uncovered 1,180 sequences, 15,172 of which included gene products, with the shortest sequence being 131 bases and maximum length 3829 base pairs. The gene list was additionally annotated using Integrated Microbial Genomes and Microbiomes. The annotation process yielded a total of 240 genes found in 177 bacterial strains. These gene products were found in the genome of strain 7598. Large volumes of data are generated using modern sequencing technology to sample all genes in all species present in a given complex sample. ConclusionsThese data revealed that it is a rich source of potential biomarkers for soybean plants. The results of this study will help us to understand the role of the endosphere microbiome in plant health and identify the microbial signatures of health and disease. The MG-RAST is a public resource for the automated phylogenetic and functional study of metagenomes. This is a powerful tool for investigating the diversity and function of microbial communities.

Viruses in deep-sea cold seep sediments harbor diverse survival mechanisms and remain genetically conserved within species

Deep sea cold seep sediments have been discovered to harbor novel, abundant, and diverse bacterial and archaeal viruses. However, little is known about viral genetic features and evolutionary patterns in these environments. Here, we examined the evolutionary ecology of viruses across active and extinct seep stages in the area of Haima cold seeps in the South China Sea. A total of 338 viral operational taxonomic units are identified and linked to 36 bacterial and archaeal phyla. The dynamics of host-virus interactions are informed by diverse antiviral defense systems across 43 families found in 487 microbial genomes. Cold seep viruses are predicted to harbor diverse adaptive strategies to persist in this environment, including counter-defense systems, auxiliary metabolic genes, reverse transcriptases, and alternative genetic code assignments. Extremely low nucleotide diversity is observed in cold seep viral populations, being influenced by factors including microbial host, sediment depth, and cold seep stage. Most cold seep viral genes are under strong purifying selection with trajectories that differ depending on whether cold seeps are active or extinct. This work sheds light on the understanding of environmental adaptation mechanisms and evolutionary patterns of viruses in the sub-seafloor biosphere.

Metagenome sequencing and 103 microbial genomes from ballast water and sediments

The great threat of microbes carried by ballast water calls for figuring out the species composition of the ballast-tank microbial community, where the dark, cold, and anoxic tank environment might select special taxa. In this study, we reconstructed 103 metagenome-assembled genomes (MAGs), including 102 bacteria and one archaea, from four vessels on international voyages. Of these MAGs, 60 were ‘near complete’ (completeness >90%), 34 were >80% complete, and nine were >75% complete. Phylogenomic analysis revealed that over 70% (n = 74) of these MAGs represented new taxa at different taxonomical levels, including one order, three families, 12 genera, and 58 species. The species composition of these MAGs was most consistent with the previous reports, with the most abundant phyla being Proteobacteria (n = 69), Bacteroidota (n = 17), and Actinobacteriota (n = 7). These draft genomes provided novel data on species diversity and function in the ballast-tank microbial community, which will facilitate ballast water and sediments management.

Microbial genome (Illumina MiSeq) sequencing of drinking water treatment residuals to evaluate compatibility with environmental applications

The clarification of drinking water leads to the production of large quantities of water treatment residuals (WTRs). DNA was extracted from six WTR samples collected from water treatment plants within the UK to compare their bacterial communities and examine whether factors such as coagulant usage (aluminium versus iron salt), the type of water source (reservoir or river), or leachable chemical composition influence these communities. Bacterial 16S variable region 4 (V4) was amplified and sequenced using Illumina MiSeq sequencing. The most abundant phyla in WTR samples were Proteobacteria, Actinobacteria, Bacteroidetes, Acidobacteria, and Firmicutes, collectively representing 92.77–97.8% of the total bacterial sequences. Statistical analysis of microbial profiles indicated that water source played a significant role in microbial community structure, diversity, and richness, however coagulant type did not. PERMANOVA analysis showed that no single chemical variable (pH, organic matter, or extractable element concentration) influenced microbial composition significantly; however, canonical correspondence analysis of WTR microbiomes yielded a model using all these variables that could be used to explain variations in microbial community structures of WTRs (p < 0.05). No common, potentially toxic cyanobacteria, or related pathogens of concern were found. Analysis with PICRUSt showed that WTRs all had similar predicted microbial functional profiles. Overall, the results indicate that WTRs analysed in this study are unlikely to pose any threat to soil microbial community structure when applied to land as a soil conditioner or enhancer and may help to enhance the soil microbial community.

Spatial and temporal metagenomics of river compartments reveals viral community dynamics in an urban impacted stream

Although river ecosystems constitute a small fraction of Earth’s total area, they are critical modulators of microbially and virally orchestrated global biogeochemical cycles. However, most studies either use data that is not spatially resolved or is collected at timepoints that do not reflect the short life cycles of microorganisms. To address this gap, we assessed how viral and microbial communities change over a 48-hour period by sampling surface water and pore water compartments of the wastewater-impacted River Erpe in Germany. We sampled every 3 hours resulting in 32 samples for which we obtained metagenomes along with geochemical and metabolite measurements. From our metagenomes, we identified 6,500 viral and 1,033 microbial metagenome assembled genomes (MAGs) and found distinct community membership and abundance associated with each river compartment (e.g., Competibacteraceae in surfacewater and Sulfurimonadaceae in pore water). We show that 17% of our viral MAGs clustered to viruses from other ecosystems like wastewater treatment plants and rivers. Our results also indicated that 70% of the viral community was persistent in surface waters, whereas only 13% were persistent in the pore waters taken from the hyporheic zone. Finally, we predicted linkages between 73 viral genomes and 38 microbial genomes. These putatively linked hosts included members of the Competibacteraceae, which we suggest are potential contributors to river carbon and nitrogen cycling via denitrification and nitrogen fixation. Together, these findings demonstrate that members of the surface water microbiome from this urban river are stable over multiple diurnal cycles. These temporal insights raise important considerations for ecosystem models attempting to constrain dynamics of river biogeochemical cycles.

A rapid genome-wide analysis of isolated giant viruses using MinION sequencing.

Following the discovery of Acanthamoeba polyphaga mimivirus, diverse giant viruses have been isolated. However, only a small fraction of these isolates have been completely sequenced, limiting our understanding of the genomic diversity of giant viruses. MinION is a portable and low-cost long-read sequencer that can be readily used in a laboratory. Although MinION provides highly error-prone reads that require correction through additional short-read sequencing, recent studies assembled high-quality microbial genomes only using MinION sequencing. Here, we evaluated the accuracy of MinION-only genome assemblies for giant viruses by re-sequencing a prototype marseillevirus. Assembled genomes presented over 99.98% identity to the reference genome with a few gaps, demonstrating a high accuracy of the MinION-only assembly. As a proof of concept, we de novo assembled five newly isolated viruses. Average nucleotide identities to their closest known relatives suggest that the isolates represent new species of marseillevirus, pithovirus and mimivirus. The assembly of subsampled reads demonstrated that their taxonomy and genomic composition could be analysed at the 50× sequencing coverage. We also identified a pithovirus gene whose homologues were detected only in metagenome-derived relatives. Collectively, we propose that MinION-only assembly is an effective approach to rapidly perform a genome-wide analysis of isolated giant viruses.

Facilitating accessible, rapid, and appropriate processing of ancient metagenomic data with AMDirT

Background: Access to sample-level metadata is important when selecting public metagenomic sequencing datasets for reuse in new biological analyses. The Standards, Precautions, and Advances in Ancient Metagenomics community (SPAAM, https://spaam-community.github.io) has previously published AncientMetagenomeDir, a collection of curated and standardised sample metadata tables for metagenomic and microbial genome datasets generated from ancient samples. However, while sample-level information is useful for identifying relevant samples for inclusion in new projects, Next Generation Sequencing (NGS) library construction and sequencing metadata are also essential for appropriately reprocessing ancient metagenomic data. Currently, recovering information for downloading and preparing such data is difficult when laboratory and bioinformatic metadata is heterogeneously recorded in prose-based publications. Methods: Through a series of community-based hackathon events, AncientMetagenomeDir was updated to provide standardised library-level metadata of existing and new ancient metagenomic samples. In tandem, the companion tool 'AMDirT' was developed to facilitate automated metadata curation and data validation, as well as rapid data filtering and downloading. Results: AncientMetagenomeDir was extended to include standardised metadata of over 5000 ancient metagenomic libraries. The companion tool 'AMDirT' provides both graphical- and command-line interface based access to such metadata for users from a wide range of computational backgrounds. We also report on errors with metadata reporting that appear to commonly occur during data upload and provide suggestions on how to improve the quality of data sharing by the community. Conclusions: Together, both standardised metadata and tooling will help towards easier incorporation and reuse of public ancient metagenomic datasets into future analyses.

Returning to Nature for the Next Generation of Antimicrobial Therapeutics.

Antibiotics found in and inspired by nature are life-saving cures for bacterial infections and have enabled modern medicine. However, the rise in resistance necessitates the discovery and development of novel antibiotics and alternative treatment strategies to prevent the return to a pre-antibiotic era. Once again, nature can serve as a source for new therapies in the form of natural product antibiotics and microbiota-based therapies. Screening of soil bacteria, particularly actinomycetes, identified most of the antibiotics used in the clinic today, but the rediscovery of existing molecules prompted a shift away from natural product discovery. Next-generation sequencing technologies and bioinformatics advances have revealed the untapped metabolic potential harbored within the genomes of environmental microbes. In this review, we first highlight current strategies for mining this untapped chemical space, including approaches to activate silent biosynthetic gene clusters and in situ culturing methods. Next, we describe how using live microbes in microbiota-based therapies can simultaneously leverage many of the diverse antimicrobial mechanisms found in nature to treat disease and the impressive efficacy of fecal microbiome transplantation and bacterial consortia on infection. Nature-provided antibiotics are some of the most important drugs in human history, and new technologies and approaches show that nature will continue to offer valuable inspiration for the next generation of antibacterial therapeutics.

Effects of Florfenicol on nirS-Type Denitrification Community Structure of Sediments in an Aquatic Microcosm Model.

Florfenicol is one of the most widely used antibiotics in aquaculture and veterinary clinics because of its low side effects and strong bactericidal effect. A total of 45~60% of florfenicol is not absorbed by the animal body and accumulates in the aquatic environment through a variety of pathways, which affects denitrification. Indoor aquatic microcosm models were constructed and sediment samples were collected at different florfenicol concentrations (0.1, 1, 10, and 100 mg/L) on days 0, 7, 30, and 60 to extract the microbial genome DNA and determine the water properties. qPCR and amplicon sequencing were used to study the dynamic changes in the nirS gene and nirS-type denitrification community structure, diversity, and abundance, respectively. The results showed that high florfenicol stress influenced the sediment's physicochemical properties, reducing conductivity, alkaline dissolved nitrogen, and organic matter content. In addition, the abundance of nirS, a functional denitrification gene, increased obviously with increased florfenicol concentrations but decreased the diversity of nirS-type denitrification microorganisms. Proteobacteria was the dominant denitrifying phylum in the sediment. Our study provides a scientific basis for the rational use of florfenicol in aquaculture to maintain a healthy and stable microecological environment and also provides a preliminary understanding of the response characteristics of water denitrifying microorganisms to florfenicol exposure.

GENETIC REDESIGN: CRISPR-CAS AND MICROBIAL GENOME EDITING

Microbial biotechnology and genome editing have undergone a revolutionary transformation with the discovery and advancement of CRISPR-Cas systems. Initially recognized as an adaptive immune system in bacteria and archaea, these systems have been repurposed into highly effective tools for accurately modifying genetic material. In this comprehensive review, we delve into the remarkable influence of CRISPR-Cas systems on microbial biotechnology and genome editing. We explore their fundamental mechanisms, recent breakthroughs, existing challenges, and future prospects in this rapidly evolving field. By unraveling the intricate workings of CRISPR-Cas systems, we shed light on their ability to facilitate precise and efficient genetic manipulation. With a focus on microbial biotechnology and genome editing, we uncover how CRISPR-Cas systems have revolutionized these areas, presenting new possibilities for genetic engineering. Moreover, we discuss the challenges CRISPR-Cas systems face, such as off-target effects and delivery methods, while highlighting the ongoing research endeavors that aim to overcome these obstacles. By examining the transformative impact of CRISPR-Cas systems, this review reveals this groundbreaking technology's immense potential and promising future in microbial biotechnology and genome editing. Keywords: CRISPR-Cas systems, microbial biotechnology, genome editing, adaptive immune system, genetic material, precise manipulation, transformative impact, off-target effects, delivery methods, genetic engineering.