Nitrate reduction to ammonium: a phylogenetic, physiological, and genetic aspects in Prokaryotes and eukaryotes.

The microbe-mediated conversion of nitrate (NO3-) to ammonium (NH4+) in the nitrogen cycle has strong implications for soil health and crop productivity. The role of prokaryotes, eukaryotes and their phylogeny, physiology, and genetic regulations are essential for understanding the ecological significance of this empirical process. Several prokaryotes (bacteria and archaea), and a few eukaryotes (fungi and algae) are reported as NO3- reducers under certain conditions. This process involves enzymatic reactions which has been catalysed by nitrate reductases, nitrite reductases, and NH4+-assimilating enzymes. Earlier reports emphasised that single-cell prokaryotic or eukaryotic organisms are responsible for this process, which portrayed a prominent gap. Therefore, this study revisits the similarities and uniqueness of mechanism behind NO3- -reduction to NH4+ in both prokaryotes and eukaryotes. Moreover, phylogenetic, physiological, and genetic regulation also shed light on the evolutionary connections between two systems which could help us to better explain the NO3--reduction mechanisms over time. Reports also revealed that certain transcription factors like NtrC/NtrB and Nit2 have shown a major role in coordinating the expression of NO3- assimilation genes in response to NO3- availability. Overall, this review provides a comprehensive information about the complex fermentative and respiratory dissimilatory nitrate reduction to ammonium (DNRA) processes. Uncovering the complexity of this process across various organisms may further give insight into sustainable nitrogen management practices and might contribute to addressing global environmental challenges.

Investigating the nature of prokaryotic genomic island locations within a genome.

Horizontal gene transfer (HGT) is a powerful evolutionary force that considerably shapes the structure of prokaryotic genomes and is associated with genomic islands (GIs). A GI is a DNA segment composed of transferred genes that can be found within a prokaryotic genome, obtained through HGT. Much research has focused on detecting GIs in genomes, but here we pursue a new course, which is identifying possible preferred locations of GIs in the prokaryotic genome. Here, we identify the locations of the GIs within prokaryotic genomes to examine patterns in those locations. Prokaryotic GIs were analyzed according to the genome structure that they are located in, whether it be a circular or a linear genome. The analytical investigations employed are: (1) studying the GI locations in relation to the origin of replication (oriC); (2) exploring the distances between GIs; and (3) determining the distribution of GIs across the genomes. For each of the investigations, the analysis was performed on all of the GIs in the data set. Moreover, to void bias caused by the distribution of the genomes represented, the GIs in one genome from each species and the GIs of the most frequent species are also analyzed. Overall, the results showed that there are preferred sites for the GIs in the genome. In the linear genomes, these sites are usually located in the oriC region and terminus region, while in the circular genomes, they are located solely in the terminus region. These results also showed that the distance distribution between the GIs is almost exponential, which proves that GIs have preferred sites within genomes. The oriC and termniuns are preferred sites for the GIs and a possible natural explanation for this could be connected to the content of the oriC region. Moreover, the content of the GIs in terms of its protein families was studied and the results demonstrated that the majority of frequent protein families are close to identical in each section.

Protein-Coding Gene Families in Prokaryote Genome Comparisons.

The identification of orthologous genes is relevant for comparative genomics, phylogenetic analysis, and functional annotation. There are many computational tools for the prediction of orthologous groups as well as web-based resources that offer orthology datasets for download and online analysis. This chapter presents a simple and practical guide to the process of orthologous group prediction, using a dataset of 10 prokaryotic proteomes as example. The orthology methods covered are OrthoMCL, COGtriangles, OrthoFinder2, and OMA. The authors compare the number of orthologous groups predicted by these various methods, and present a brief workflow for the functional annotation and reconstruction of phylogenies from inferred single-copy orthologous genes. The chapter also demonstrates how to explore two orthology databases: eggNOG6 and OrthoDB.

Annotation and Comparative Genomics of Prokaryotic Transposable Elements.

The data generated in nearly 30 years of bacterial genome sequencing has revealed the abundance of transposable elements (TE) and their importance in genome and transcript remodeling through the mediation of DNA insertions and deletions, structural rearrangements, and regulation of gene expression. Furthermore, what we have learned from studying transposition mechanisms and their regulation in bacterial TE is fundamental to our current understanding of TE in other organisms because much of what has been observed in bacteria is conserved in all domains of life. However, unlike eukaryotic TE, prokaryotic TE sequester and transmit important classes of genes that impact host fitness, such as resistance to antibiotics and heavy metals and virulence factors affecting animals and plants, among other acquired traits. This provides dynamism and plasticity to bacteria, which would otherwise be propagated clonally. The insertion sequences (IS), the simplest form of prokaryotic TE, are autonomous and compact mobile genetic elements. These can be organized into compound transposons, in which two similar IS can flank any DNA segment and render it transposable. Other more complex structures, called unit transposons, can be grouped into four major families (Tn3, Tn7, Tn402, Tn554) with specific genetic characteristics. This chapter will revisit the prominent structural features of these elements, focusing on a genomic annotation framework and comparative analysis. Relevant aspects of TE will also be presented, stressing their key position in genome impact and evolution, especially in the emergence of antimicrobial resistance and other adaptive traits.

Substrate uptake patterns shape niche separation in marine prokaryotic microbiome.

Marine heterotrophic prokaryotes primarily take up ambient substrates using transporters. The patterns of transporters targeting particular substrates shape the ecological role of heterotrophic prokaryotes in marine organic matter cycles. Here, we report a size-fractionated pattern in the expression of prokaryotic transporters throughout the oceanic water column due to taxonomic variations, revealed by a multi-"omics" approach targeting ATP-binding cassette (ABC) transporters and TonB-dependent transporters (TBDTs). Substrate specificity analyses showed that marine SAR11, Rhodobacterales, and Oceanospirillales use ABC transporters to take up organic nitrogenous compounds in the free-living fraction, while Alteromonadales, Bacteroidetes, and Sphingomonadales use TBDTs for carbon-rich organic matter and metal chelates on particles. The expression of transporter proteins also supports distinct lifestyles of deep-sea prokaryotes. Our results suggest that transporter divergency in organic matter assimilation reflects a pronounced niche separation in the prokaryote-mediated organic matter cycles.

Macroalgal virosphere assists with host-microbiome equilibrium regulation and affects prokaryotes in surrounding marine environments.

The microbiomes in macroalgal holobionts play vital roles in regulating macroalgal growth and ocean carbon cycling. However, the virospheres in macroalgal holobionts remain largely underexplored, representing a critical knowledge gap. Here we unveil that the holobiont of kelp (Saccharina japonica) harbors highly specific and unique epiphytic/endophytic viral species, with novelty (99.7% unknown) surpassing even extreme marine habitats (e.g. deep-sea and hadal zones), indicating that macroalgal virospheres, despite being closest to us, are among the least understood. These viruses potentially maintain microbiome equilibrium critical for kelp health via lytic-lysogenic infections and the expression of folate biosynthesis genes. In-situ kelp mesocosm cultivation and metagenomic mining revealed that kelp holobiont profoundly reshaped surrounding seawater and sediment virus-prokaryote pairings through changing surrounding environmental conditions and virus-host migrations. Some kelp epiphytic viruses could even infect sediment autochthonous bacteria after deposition. Moreover, the presence of ample viral auxiliary metabolic genes for kelp polysaccharide (e.g. laminarin) degradation underscores the underappreciated viral metabolic influence on macroalgal carbon cycling. This study provides key insights into understanding the previously overlooked ecological significance of viruses within macroalgal holobionts and the macroalgae-prokaryotes-virus tripartite relationship.

Light Control in Microbial Systems.

Light is a key environmental component influencing many biological processes, particularly in prokaryotes such as archaea and bacteria. Light control techniques have revolutionized precise manipulation at molecular and cellular levels in recent years. Bacteria, with adaptability and genetic tractability, are promising candidates for light control studies. This review investigates the mechanisms underlying light activation in bacteria and discusses recent advancements focusing on light control methods and techniques for controlling bacteria. We delve into the mechanisms by which bacteria sense and transduce light signals, including engineered photoreceptors and light-sensitive actuators, and various strategies employed to modulate gene expression, protein function, and bacterial motility. Furthermore, we highlight recent developments in light-integrated methods of controlling microbial responses, such as upconversion nanoparticles and optical tweezers, which can enhance the spatial and temporal control of bacteria and open new horizons for biomedical applications.

DeepReg: a deep learning hybrid model for predicting transcription factors in eukaryotic and prokaryotic genomes.

Deep learning models (DLMs) have gained importance in predicting, detecting, translating, and classifying a diversity of inputs. In bioinformatics, DLMs have been used to predict protein structures, transcription factor-binding sites, and promoters. In this work, we propose a hybrid model to identify transcription factors (TFs) among prokaryotic and eukaryotic protein sequences, named Deep Regulation (DeepReg) model. Two architectures were used in the DL model: a convolutional neural network (CNN), and a bidirectional long-short-term memory (BiLSTM). DeepReg reached a precision of 0.99, a recall of 0.97, and an F1-score of 0.98. The quality of our predictions, the bias-variance trade-off approach, and the characterization of new TF predictions were evaluated and compared against those produced by DeepTFactor, as well as against experimental data from three model organisms. Predictions based on our DLM tended to exhibit less variance and bias than those from DeepTFactor, thus increasing reliability and decreasing overfitting.

Can Sb(III)-oxidizing prokaryote also oxidize As(III) under aerobic and anaerobic conditions, and vice versa?

Sb(III) and As(III) share similar chemical features and coexist in the environment. However, their oxidase enzymes have completely different sequences and structures. This raises an intriguing question: Could Sb(III)-oxidizing prokaryotes (SOPs) also oxidize As(III), and vice versa? Regarding this issue, previous investigations have yielded unclear, incorrect and even conflicting data. This work aims to address this matter. First, we prepared an enriched population of SOPs that comprises 55 different AnoA genes, lacking AioAB and ArxAB genes. We found that these SOPs can oxidize both Sb(III) and As(III) with comparable capabilities. To further confirm this finding, we isolated three cultivable SOP strains that have AnoA gene, but lack AioAB and ArxAB genes. We observed that they also oxidize both Sb(III) and As(III) under both anaerobic and aerobic conditions. Secondly, we obtained an enriched population of As(III)-oxidizing prokaryotes (AOPs) from As-contaminated soils, which comprises 69 different AioA genes, lacking AnoA gene. We observed that the AOP population has significant As(III)-oxidizing activities, but lack detectable Sb(III)-oxidizing activities under both aerobic and anaerobic conditions. Therefore, we convincingly show that SOPs can oxidize As(III), but AOPs cannot oxidize Sb(III). These findings clarify the previous ambiguities, confusion, errors or contradictions regarding how SOPs and AOPs oxidize each other's substrate.

IPEV: identification of prokaryotic and eukaryotic virus-derived sequences in virome using deep learning.

BACKGROUND: The virome obtained through virus-like particle enrichment contains a mixture of prokaryotic and eukaryotic virus-derived fragments. Accurate identification and classification of these elements are crucial to understanding their roles and functions in microbial communities. However, the rapid mutation rates of viral genomes pose challenges in developing high-performance tools for classification, potentially limiting downstream analyses. FINDINGS: We present IPEV, a novel method to distinguish prokaryotic and eukaryotic viruses in viromes, with a 2-dimensional convolutional neural network combining trinucleotide pair relative distance and frequency. Cross-validation assessments of IPEV demonstrate its state-of-the-art precision, significantly improving the F1-score by approximately 22% on an independent test set compared to existing methods when query viruses share less than 30% sequence similarity with known viruses. Furthermore, IPEV outperforms other methods in accuracy on marine and gut virome samples based on annotations by sequence alignments. IPEV reduces runtime by at most 1,225 times compared to existing methods under the same computing configuration. We also utilized IPEV to analyze longitudinal samples and found that the gut virome exhibits a higher degree of temporal stability than previously observed in persistent personal viromes, providing novel insights into the resilience of the gut virome in individuals. CONCLUSIONS: IPEV is a high-performance, user-friendly tool that assists biologists in identifying and classifying prokaryotic and eukaryotic viruses within viromes. The tool is available at https://github.com/basehc/IPEV.

POCP-nf: an automatic Nextflow pipeline for calculating the percentage of conserved proteins in bacterial taxonomy.

SUMMARY: Sequence technology advancements have led to an exponential increase in bacterial genomes, necessitating robust taxonomic classification methods. The Percentage Of Conserved Proteins (POCP), proposed initially by Qin et al. (2014), is a valuable metric for assessing prokaryote genus boundaries. Here, I introduce a computational pipeline for automated POCP calculation, aiming to enhance reproducibility and ease of use in taxonomic studies. AVAILABILITY AND IMPLEMENTATION: The POCP-nf pipeline uses DIAMOND for faster protein alignments, achieving similar sensitivity to BLASTP. The pipeline is implemented in Nextflow with Conda and Docker support and is freely available on GitHub under https://github.com/hoelzer/pocp. The open-source code can be easily adapted for various prokaryotic genome and protein datasets. Detailed documentation and usage instructions are provided in the repository.

Functional Roles and Genomic Impact of Miniature Inverted-Repeat Transposable Elements (MITEs) in Prokaryotes.

Prokaryotic genomes are dynamic tapestries that are strongly influenced by mobile genetic elements (MGEs), including transposons (Tn's), plasmids, and bacteriophages. Of these, miniature inverted-repeat transposable elements (MITEs) are undoubtedly the least studied MGEs in bacteria and archaea. This review explores the diversity and distribution of MITEs in prokaryotes and describes what is known about their functional roles in the host and involvement in genomic plasticity and evolution.

Exploring the prokaryote-eukaryote interplay in microbial mats from an Andean athalassohaline wetland.

Microbial community assembly results from the interaction between biotic and abiotic factors. However, environmental selection is thought to predominantly shape communities in extreme ecosystems. Salar de Huasco, situated in the high-altitude Andean Altiplano, represents a poly-extreme ecosystem displaying spatial gradients of physicochemical conditions. To disentangle the influence of abiotic and biotic factors, we studied prokaryotic and eukaryotic communities from microbial mats and underlying sediments across contrasting areas of this athalassohaline ecosystem. The prokaryotic communities were primarily composed of bacteria, notably including a significant proportion of photosynthetic organisms like Cyanobacteria and anoxygenic photosynthetic members of Alpha- and Gammaproteobacteria and Chloroflexi. Additionally, Bacteroidetes, Verrucomicrobia, and Deltaproteobacteria were abundantly represented. Among eukaryotes, photosynthetic organisms (Ochrophyta and Archaeplastida) were predominant, alongside relatively abundant ciliates, cercozoans, and flagellated fungi. Salinity emerged as a key driver for the assembly of prokaryotic communities. Collectively, abiotic factors influenced both prokaryotic and eukaryotic communities, particularly those of algae. However, prokaryotic communities strongly correlated with photosynthetic eukaryotes, suggesting a pivotal role of biotic interactions in shaping these communities. Co-occurrence networks suggested potential interactions between different organisms, such as diatoms with specific photosynthetic and heterotrophic bacteria or with protist predators, indicating influences beyond environmental selection. While some associations may be explained by environmental preferences, the robust biotic correlations, alongside insights from other ecosystems and experimental studies, suggest that symbiotic and trophic interactions significantly shape microbial mat and sediment microbial communities in this athalassohaline ecosystem.IMPORTANCEHow biotic and abiotic factors influence microbial community assembly is still poorly defined. Here, we explore their influence on prokaryotic and eukaryotic community assembly within microbial mats and sediments of an Andean high-altitude polyextreme wetland system. We show that, in addition to abiotic elements, mutual interactions exist between prokaryotic and eukaryotic communities. Notably, photosynthetic eukaryotes exhibit a strong correlation with prokaryotic communities, specifically diatoms with certain bacteria and other protists. Our findings underscore the significance of biotic interactions in community assembly and emphasize the necessity of considering the complete microbial community.

Co-transcriptional gene regulation in eukaryotes and prokaryotes.

Many steps of RNA processing occur during transcription by RNA polymerases. Co-transcriptional activities are deemed commonplace in prokaryotes, in which the lack of membrane barriers allows mixing of all gene expression steps, from transcription to translation. In the past decade, an extraordinary level of coordination between transcription and RNA processing has emerged in eukaryotes. In this Review, we discuss recent developments in our understanding of co-transcriptional gene regulation in both eukaryotes and prokaryotes, comparing methodologies and mechanisms, and highlight striking parallels in how RNA polymerases interact with the machineries that act on nascent RNA. The development of RNA sequencing and imaging techniques that detect transient transcription and RNA processing intermediates has facilitated discoveries of transcription coordination with splicing, 3'-end cleavage and dynamic RNA folding and revealed physical contacts between processing machineries and RNA polymerases. Such studies indicate that intron retention in a given nascent transcript can prevent 3'-end cleavage and cause transcriptional readthrough, which is a hallmark of eukaryotic cellular stress responses. We also discuss how coordination between nascent RNA biogenesis and transcription drives fundamental aspects of gene expression in both prokaryotes and eukaryotes.

Oxygen-dependent biofilm dynamics in leaf decay: an in vitro analysis.

Biofilms are important in the natural process of plant tissue degradation. However, fundamental knowledge of biofilm community structure and succession on decaying leaves under different oxygen conditions is limited. Here, we used 16S rRNA and ITS gene amplicon sequencing to investigate the composition, temporal dynamics, and community assembly processes of bacterial and fungal biofilms on decaying leaves in vitro. Leaves harvested from three plant species were immersed in lake water under aerobic and anaerobic conditions in vitro for three weeks. Biofilm-covered leaf samples were collected weekly and investigated by scanning electron microscopy. The results showed that community composition differed significantly between biofilm samples under aerobic and anaerobic conditions, though not among plant species. Over three weeks, a clear compositional shift of the bacterial and fungal biofilm communities was observed. The alpha diversity of prokaryotes increased over time in aerobic assays and decreased under anaerobic conditions. Oxygen availability and incubation time were found to be primary factors influencing the microbial diversity of biofilms on different decaying plant species in vitro. Null models suggest that stochastic processes governed the assembly of biofilm communities of decaying leaves in vitro in the early stages of biofilm formation and were further shaped by niche-associated factors.

Speeding genomic island discovery through systematic design of reference database composition.

BACKGROUND: Genomic islands (GIs) are mobile genetic elements that integrate site-specifically into bacterial chromosomes, bearing genes that affect phenotypes such as pathogenicity and metabolism. GIs typically occur sporadically among related bacterial strains, enabling comparative genomic approaches to GI identification. For a candidate GI in a query genome, the number of reference genomes with a precise deletion of the GI serves as a support value for the GI. Our comparative software for GI identification was slowed by our original use of large reference genome databases (DBs). Here we explore smaller species-focused DBs. RESULTS: With increasing DB size, recovery of our reliable prophage GI calls reached a plateau, while recovery of less reliable GI calls (FPs) increased rapidly as DB sizes exceeded ~500 genomes; i.e., overlarge DBs can increase FP rates. Paradoxically, relative to prophages, FPs were both more frequently supported only by genomes outside the species and more frequently supported only by genomes inside the species; this may be due to their generally lower support values. Setting a DB size limit for our SMAll Ranked Tailored (SMART) DB design speeded runtime ~65-fold. Strictly intra-species DBs would tend to lower yields of prophages for small species (with few genomes available); simulations with large species showed that this could be partially overcome by reaching outside the species to closely related taxa, without an FP burden. Employing such taxonomic outreach in DB design generated redundancy in the DB set; as few as 2984 DBs were needed to cover all 47894 prokaryotic species. CONCLUSIONS: Runtime decreased dramatically with SMART DB design, with only minor losses of prophages. We also describe potential utility in other comparative genomics projects.

Bacterial symbionts of the precious coral Corallium rubrum are differentially distributed across colony-specific compartments and differ among colormorphs.

Corals engage in symbioses with micro-organisms that provide nutrients and protect the host. Where the prokaryotic microbes perform their symbiotic functions within a coral is, however, poorly understood. Here, we studied the tissue-specific microbiota of the coral Corallium rubrum by dissecting its tissues from the skeleton and separating the white polyps from the red-coloured coenenchyme, followed by 16S rRNA gene metabarcoding of the three fractions. Dissection was facilitated by incubating coral fragments in RNAlater, which caused tissues to detach from the skeleton. Our results show compartmentalisation of the microbiota. Specifically, Endozoicomonas, Parcubacteria and a Gammaproteobacteria were primarily located in polyps, whereas Nitrincolaceae and one Spirochaeta phylotype were found mainly in the coenenchyme. The skeleton-associated microbiota was distinct from the microbiota in the tissues. Given the difference in tissue colour and microbiota of the polyps and coenenchyme, we analysed the microbiota of three colormorphs of C. rubrum (red, pink, white), finding that the main difference was a very low abundance of Spirochaeta in white colormorphs. While the functions of C. rubrum's symbionts are unknown, their localisation within the colony suggests that microhabitats exist, and the presence of Spirochaeta appears to be linked to the colour of C. rubrum.

The Constructive Black Queen hypothesis: new functions can evolve under conditions favouring gene loss.

Duplication is a major route for the emergence of new gene functions. However, the emergence of new gene functions via this route may be reduced in prokaryotes, as redundant genes are often rapidly purged. In lineages with compact, streamlined genomes, it thus appears challenging for novel function to emerge via duplication and divergence. A further pressure contributing to gene loss occurs under Black Queen dynamics, as cheaters that lose the capacity to produce a public good can instead acquire it from neighbouring producers. We propose that Black Queen dynamics can favour the emergence of new function because, under an emerging Black Queen dynamic, there is high gene redundancy spread across a community of interacting cells. Using computational modelling, we demonstrate that new gene functions can emerge under Black Queen dynamics. This result holds even if there is deletion bias due to low duplication rates and selection against redundant gene copies resulting from the high cost associated with carrying a locus. However, when the public good production costs are high, Black Queen dynamics impede the fixation of new functions. Our results expand the mechanisms by which new gene functions can emerge in prokaryotic systems.

Adaptive response of prokaryotic communities to extreme pollution flooding in a Paleolithic rock art cave (Pindal Cave, northern Spain).

A flood event affecting Pindal Cave, a UNESCO World Heritage site, introduced a substantial amount of external sediments and waste into the cave. This event led to the burial of preexisting sediments, altering the biogeochemical characteristics of the cave ecosystem by introducing heightened levels of organic matter, nitrogen compounds, phosphorus, and heavy metals. The sediments included particulate matter and waste from a cattle farm located within the water catchment area of the cavity, along with diverse microorganisms, reshaping the cave microbial community. This study addresses the ongoing influence of a cattle farm on the cave ecosystem and aims to understand the adaptive responses of the underground microbial community to the sudden influx of waste allochthonous material. Here, we show that the flood event had an immediate and profound effect on the cave microbial community, marked by a significant increase in methanogenic archaea, denitrifying bacteria, and other microorganisms commonly associated with mammalian intestinal tracts. Furthermore, our findings reveal that one year after the flood, microorganisms related to the flood decreased, while the increase in inorganic forms of ammonium and nitrate suggests potential nitrification, aligning with increased abundances of corresponding functional genes involved in nitrogen cycling. The results reveal that the impact of pollution was neither recent nor isolated, and it was decisive in stopping livestock activity near the cave. The influence of the cattle farm has persisted since its establishment over the impluvium area, and this influence endures even a year after the flood. Our study emphasizes the dynamic interplay between natural events, anthropogenic activities, and microbial communities, offering insights into the resilience of cave ecosystems. Understanding microbial adaptation in response to environmental disturbances, as demonstrated in this cave ecosystem, has implications for broader ecological studies and underscores the importance of considering temporal dynamics in conservation efforts.