Hi-C/3C-seq Data Analysis for Prokaryotic Genomes with HiC-Pro.

Hi-C and 3C-seq are powerful tools to study the 3D genomes of bacteria and archaea, whose small cell sizes and growth conditions are often intractable to detailed microscopic analysis. However, the circularity of prokaryotic genomes requires a number of tricks for Hi-C/3C-seq data analysis. Here, I provide a practical guide to use the HiC-Pro pipeline for Hi-C/3C-seq data obtained from prokaryotes.

Deepdefense: annotation of immune systems in prokaryotes using deep learning.

BACKGROUND: Due to a constant evolutionary arms race, archaea and bacteria have evolved an abundance and diversity of immune responses to protect themselves against phages. Since the discovery and application of CRISPR-Cas adaptive immune systems, numerous novel candidates for immune systems have been identified. Previous approaches to identifying these new immune systems rely on hidden Markov model (HMM)-based homolog searches or use labor-intensive and costly wet-lab experiments. To aid in finding and classifying immune systems genomes, we use machine learning to classify already known immune system proteins and discover potential candidates in the genome. Neural networks have shown promising results in classifying and predicting protein functionality in recent years. However, these methods often operate under the closed-world assumption, where it is presumed that all potential outcomes or classes are already known and included in the training dataset. This assumption does not always hold true in real-world scenarios, such as in genomics, where new samples can emerge that were not previously accounted for in the training phase. RESULTS: In this work, we explore neural networks for immune protein classification, deal with different methods for rejecting unrelated proteins in a genome-wide search, and establish a benchmark. Then, we optimize our approach for accuracy. Based on this, we develop an algorithm called Deepdefense to predict immune cassette classes based on a genome. This design facilitates the differentiation between immune system-related and unrelated proteins by analyzing variations in model-predicted confidence values, aiding in the identification of both known and potentially novel immune system proteins. Finally, we test our approach for detecting immune systems in the genome against an HMM-based method. CONCLUSIONS: Deepdefense can automatically detect genes and define cassette annotations and classifications using 2 model classifications. This is achieved by creating an optimized deep learning model to annotate immune systems, in combination with calibration methods, and a second model to enable the scanning of an entire genome.

The emerging view on the origin and early evolution of eukaryotic cells.

The origin of the eukaryotic cell, with its compartmentalized nature and generally large size compared with bacterial and archaeal cells, represents a cornerstone event in the evolution of complex life on Earth. In a process referred to as eukaryogenesis, the eukaryotic cell is believed to have evolved between approximately 1.8 and 2.7 billion years ago from its archaeal ancestors, with a symbiosis with a bacterial (proto-mitochondrial) partner being a key event. In the tree of life, the branch separating the first from the last common ancestor of all eukaryotes is long and lacks evolutionary intermediates. As a result, the timing and driving forces of the emergence of complex eukaryotic features remain poorly understood. During the past decade, environmental and comparative genomic studies have revealed vital details about the identity and nature of the host cell and the proto-mitochondrial endosymbiont, enabling a critical reappraisal of hypotheses underlying the symbiotic origin of the eukaryotic cell. Here we outline our current understanding of the key players and events underlying the emergence of cellular complexity during the prokaryote-to-eukaryote transition and discuss potential avenues of future research that might provide new insights into the enigmatic origin of the eukaryotic cell.

Introduction to the Special Issue on Early Evolution and the Last Common Ancestor.

The early evolution of life spans an extensive period preceding the emergence of the first eukaryotic cell. This epoch, which transpired from 4.5 to 2.5 billion years ago, marked the advent of many fundamental cellular attributes and witnessed the existence of the Last Common Ancestor (LCA) of all life forms. Uncovering and reconstructing this elusive LCA's characteristics and genetic makeup represents a formidable challenge and a pivotal pursuit in early evolution. While most scientific accounts concur that the LCA resembles contemporary prokaryotes, its precise definition, genome composition, metabolic capabilities, and ecological niche remain subjects of contentious debate.

Resistance-based directed evolution of nanobodies for higher affinity in prokaryotes.

A prokaryotic resistance-based directed evolution system leveraging protein-fragment complementation assay (PCA) was devised, and its proficiency in detecting protein-protein interactions and discriminating varying degrees of binding affinity was demonstrated by two well-characterized protein pairs. Furthermore, we constructed a random mutant library based on the GBPR36K/E45K mutant, characterized by almost no affinity towards EGFP. This library was subjected to PCA-based prokaryotic directed evolution, resulting in the isolation of back-mutated variants. In summary, we have established an expedited, cost-effective, and structural information-independent PCA-based prokaryotic directed evolution platform for nanobody affinity maturation, featuring tunable screening stringency via modulation of antibiotic concentrations.

Proposal to add a Note to Rule 8 of the International Code of Nomenclature of Prokaryotes to clarify the meaning of the term 'stem'.

According to the Rules of the International Code of Nomenclature of Prokaryotes (ICNP) and its appendices, names of higher taxa are formed by the addition of the appropriate suffix to the stem of the name of the type genus, and word stems derived from Latin and/or Greek are combined to compound names by means of an appropriate connecting vowel. The way the word 'stem' is used in the ICNP differs from the meaning of this term in textbooks of Latin and Greek grammar. We therefore propose to add a Note to Rule 8, clarifying that the term 'stem' when used in the ICNP corresponds with that part of the word that does not vary among the forms of the noun in the oblique cases, i.e., cases other than the nominative, and which can be obtained by deleting the ending of the genitive singular.

The dynamic history of prokaryotic phyla: discovery, diversity and division.

Here, I review the dynamic history of prokaryotic phyla. Following leads set by Darwin, Haeckel and Woese, the concept of phylum has evolved from a group sharing common phenotypes to a set of organisms sharing a common ancestry, with modern taxonomy based on phylogenetic classifications drawn from macromolecular sequences. Phyla came as surprising latecomers to the formalities of prokaryotic nomenclature in 2021. Since then names have been validly published for 46 prokaryotic phyla, replacing some established names with neologisms, prompting criticism and debate within the scientific community. Molecular barcoding enabled phylogenetic analysis of microbial ecosystems without cultivation, leading to the identification of candidate divisions (or phyla) from diverse environments. The introduction of metagenome-assembled genomes marked a significant advance in identifying and classifying uncultured microbial phyla. The lumper-splitter dichotomy has led to disagreements, with experts cautioning against the pressure to create a profusion of new phyla and prominent databases adopting a conservative stance. The Candidatus designation has been widely used to provide provisional status to uncultured prokaryotic taxa, with phyla named under this convention now clearly surpassing those with validly published names. The Genome Taxonomy Database (GTDB) has offered a stable, standardized prokaryotic taxonomy with normalized taxonomic ranks, which has led to both lumping and splitting of pre-existing phyla. The GTDB framework introduced unwieldy alphanumeric placeholder labels, prompting recent publication of over 100 user-friendly Latinate names for unnamed prokaryotic phyla. Most candidate phyla remain 'known unknowns', with limited knowledge of their genomic diversity, ecological roles, or environments. Whether phyla still reflect significant evolutionary and ecological partitions across prokaryotic life remains an area of active debate. However, phyla remain of practical importance for microbiome analyses, particularly in clinical research. Despite potential diminishing returns in discovery of biodiversity, prokaryotic phyla offer extensive research opportunities for microbiologists for the foreseeable future.

Histones and histone variant families in prokaryotes.

Histones are important chromatin-organizing proteins in eukaryotes and archaea. They form superhelical structures around which DNA is wrapped. Recent studies have shown that some archaea and bacteria contain alternative histones that exhibit different DNA binding properties, in addition to highly divergent sequences. However, the vast majority of these histones are identified in metagenomes and thus are difficult to study in vivo. The recent revolutionary breakthroughs in computational protein structure prediction by AlphaFold2 and RoseTTAfold allow for unprecedented insights into the potential function and structure of previously uncharacterized proteins. Here, we categorize the prokaryotic histone space into 17 distinct groups based on AlphaFold2 predictions. We identify a superfamily of histones, termed α3 histones, which are common in archaea and present in several bacteria. Importantly, we establish the existence of a large family of histones throughout archaea and in some bacteriophages that, instead of wrapping DNA, bridge DNA, thereby diverging from conventional nucleosomal histones.

Community organization and network complexity and stability: contrasting strategies of prokaryotic versus eukaryotic microbiomes in the Bohai Sea and Yellow Sea.

Unraveling the effects of spatial gradients on microbiome assembly and association is a challenging topic that remains understudied in the coastal ecosystem. Here, we aimed to investigate the effects of spatial variation on the network complexity and stability of plankton microbiomes in the Bohai Sea and Yellow Sea. These seas serve as spawning and nursery grounds for economically important fisheries valued at billions of dollars annually. Environmental heterogeneity structures microbial communities into distinct spatial patterns, leading to complex direct/indirect relationships and broader ecological niches of bacterioplankton compared to microeukaryotic communities. Interestingly, salinity gradients positively influenced the richness of rare subgroups of bacterioplankton, while the rare microeukaryotic subgroups showed an opposite trend. Abundant subgroups of prokaryotic/eukaryotic microbiomes exhibited greater environmental niche breadth and lower phylogenetic distance compared to the rare subgroups. Stochastic processes contributed greatly to microbiome dynamics, and deterministic processes governed the bacterioplankton organization with a lower phylogenetic turnover rate. Compared to microeukaryotes, bacterioplankton exhibit higher network modularity, complexity, and robustness and lower fragmentation, and vulnerability. These observations offer vital insights into the anti-interference ability and resistance of plankton microbiomes in response to environmental gradients in terms of organization and survival strategy as well as their adaptability to environmental disturbances.IMPORTANCEAn in-depth understanding of community organization and stability of coastal microbiomes is crucial to determining the sustainability of marine ecosystems, such as the Bohai Sea and Yellow Sea. Distinct responses between prokaryotic and eukaryotic microbiomes to spatial heterogeneity were observed in terms of geographical distribution, phylogenetic distance, niche breadth, and community assembly process. Environmental variations are significantly correlated with the dynamics of rare eukaryotic plankton subcommunities compared to prokaryotic plankton subcommunities. Deterministic processes shaped prokaryotic plankton community organization with a lower phylogenic turnover rate. Rare subgroups had noticeably higher phylogenetic distance and lower niche breadth than the corresponding abundant subgroups. Prokaryotic microbiomes had higher molecular network complexity and stability compared to microeukaryotes. Results presented here show how environmental gradients alter both the geographical characteristics of the microbial organization in coastal seas and also their co-occurrence network complexity and stability and thus have critical implications for nutrient and energy cycling.

Cracking the Code: Reprogramming the Genetic Script in Prokaryotes and Eukaryotes to Harness the Power of Noncanonical Amino Acids.

Over 500 natural and synthetic amino acids have been genetically encoded in the last two decades. Incorporating these noncanonical amino acids into proteins enables many powerful applications, ranging from basic research to biotechnology, materials science, and medicine. However, major challenges remain to unleash the full potential of genetic code expansion across disciplines. Here, we provide an overview of diverse genetic code expansion methodologies and systems and their final applications in prokaryotes and eukaryotes, represented by Escherichia coli and mammalian cells as the main workhorse model systems. We highlight the power of how new technologies can be first established in simple and then transferred to more complex systems. For example, whole-genome engineering provides an excellent platform in bacteria for enabling transcript-specific genetic code expansion without off-targets in the transcriptome. In contrast, the complexity of a eukaryotic cell poses challenges that require entirely new approaches, such as striving toward establishing novel base pairs or generating orthogonally translating organelles within living cells. We connect the milestones in expanding the genetic code of living cells for encoding novel chemical functionalities to the most recent scientific discoveries, from optimizing the physicochemical properties of noncanonical amino acids to the technological advancements for their in vivo incorporation. This journey offers a glimpse into the promising developments in the years to come.

Prokaryotic-virus-encoded auxiliary metabolic genes throughout the global oceans.

BACKGROUND: Prokaryotic microbes have impacted marine biogeochemical cycles for billions of years. Viruses also impact these cycles, through lysis, horizontal gene transfer, and encoding and expressing genes that contribute to metabolic reprogramming of prokaryotic cells. While this impact is difficult to quantify in nature, we hypothesized that it can be examined by surveying virus-encoded auxiliary metabolic genes (AMGs) and assessing their ecological context. RESULTS: We systematically developed a global ocean AMG catalog by integrating previously described and newly identified AMGs and then placed this catalog into ecological and metabolic contexts relevant to ocean biogeochemistry. From 7.6 terabases of Tara Oceans paired prokaryote- and virus-enriched metagenomic sequence data, we increased known ocean virus populations to 579,904 (up 16%). From these virus populations, we then conservatively identified 86,913 AMGs that grouped into 22,779 sequence-based gene clusters, 7248 (~ 32%) of which were not previously reported. Using our catalog and modeled data from mock communities, we estimate that ~ 19% of ocean virus populations carry at least one AMG. To understand AMGs in their metabolic context, we identified 340 metabolic pathways encoded by ocean microbes and showed that AMGs map to 128 of them. Furthermore, we identified metabolic "hot spots" targeted by virus AMGs, including nine pathways where most steps (≥ 0.75) were AMG-targeted (involved in carbohydrate, amino acid, fatty acid, and nucleotide metabolism), as well as other pathways where virus-encoded AMGs outnumbered cellular homologs (involved in lipid A phosphates, phosphatidylethanolamine, creatine biosynthesis, phosphoribosylamine-glycine ligase, and carbamoyl-phosphate synthase pathways). CONCLUSIONS: Together, this systematically curated, global ocean AMG catalog and analyses provide a valuable resource and foundational observations to understand the role of viruses in modulating global ocean metabolisms and their biogeochemical implications. Video Abstract.

Uncoated gold nanoparticles create fewer and less localized defects in model prokaryotic than in model eukaryotic lipid membranes.

The rise of the populations of antibiotic resistant bacteria represents an increasing threat to human health. In addition to the synthesis of new antibiotics, which is an extremely expensive and time-consuming process, one of the ways to combat bacterial infections is the use of gold nanoparticles (Au NPs) as the vehicles for targeted delivery of therapeutic drugs. Since such a strategy requires the investigation of the effect of Au NPs (with and without drugs) on both bacterial and human cells, we investigated how the presence of coating-free Au NPs affects the physicochemical properties of lipid membranes that model prokaryotic (PRO) and eukaryotic (EU) cells. PRO/EU systems prepared as multilamellar liposomes (MLVs) and hybrid structures (HSs) from 1,2-dipalmitoyl-sn-glycero-3-phosphocholine (DPPC) and 1,2-dipalmitoyl-sn-glycero-3-phosphatidylglycerol (DPPG)/1,2-dipalmitoyl-sn-glycero-3-phosphoserine (DPPS) in the absence (MLVs)/presence (HSs) of differently distributed Au NPs (sizes ∼20 nm) reported stabilization of the gel phase of PRO systems in comparison with EU one (DSC data of PRO/EU were Tm(MLVs) ≈ 41.8 °C/42.0 °C, Tm¯ (HSs) ≈ 43.1 °C/42.4 °C, whereas UV-Vis response Tm(MLVs) ≈ 41.5 °C/42.0 °C, Tm¯ (HSs) ≈ 42.9 °C/41.1 °C). Vibrational spectroscopic data unraveled a substantial impact of Au NPs on the non-polar part of lipid bilayers, emphasizing the increase of kink and gauche conformers of the hydrocarbon chain. By interpreting the latter as Au NPs-induced defects, which exert the greatest effect when Au NPs are found exclusively outside the lipid membrane, these findings suggested that Au NPs reduced the compactness of EU-based lipid bilayers much more than in analogous PRO systems. Since the uncoated Au NPs manifested adverse effects when applied as antimicrobials, the results obtained in this work contribute towards recognizing AuNP functionalization as a strategy in tuning and reversing this effect.

Predicting Promoters in Multiple Prokaryotes with Prompt.

Promoters are important cis-regulatory elements for the regulation of gene expression, and their accurate predictions are crucial for elucidating the biological functions and potential mechanisms of genes. Many previous prokaryotic promoter prediction methods are encouraging in terms of the prediction performance, but most of them focus on the recognition of promoters in only one or a few bacterial species. Moreover, due to ignoring the promoter sequence motifs, the interpretability of predictions with existing methods is limited. In this work, we present a generalized method Prompt (Promoters in multiple prokaryotes) to predict promoters in 16 prokaryotes and improve the interpretability of prediction results. Prompt integrates three methods including RSK (Regression based on Selected k-mer), CL (Contrastive Learning) and MLP (Multilayer Perception), and employs a voting strategy to divide the datasets into high-confidence and low-confidence categories. Results on the promoter prediction tasks in 16 prokaryotes show that the accuracy (Accuracy, Matthews correlation coefficient) of Prompt is greater than 80% in highly credible datasets of 16 prokaryotes, and is greater than 90% in 12 prokaryotes, and Prompt performs the best compared with other existing methods. Moreover, by identifying promoter sequence motifs, Prompt can improve the interpretability of the predictions. Prompt is freely available at https://github.com/duqimeng/PromptPrompt , and will contribute to the research of promoters in prokaryote.

The global distribution and climate resilience of marine heterotrophic prokaryotes.

Heterotrophic Bacteria and Archaea (prokaryotes) are a major component of marine food webs and global biogeochemical cycles. Yet, there is limited understanding about how prokaryotes vary across global environmental gradients, and how their global abundance and metabolic activity (production and respiration) may be affected by climate change. Using global datasets of prokaryotic abundance, cell carbon and metabolic activity we reveal that mean prokaryotic biomass varies by just under 3-fold across the global surface ocean, while total prokaryotic metabolic activity increases by more than one order of magnitude from polar to tropical coastal and upwelling regions. Under climate change, global prokaryotic biomass in surface waters is projected to decline ~1.5% per °C of warming, while prokaryotic respiration will increase ~3.5% ( ~ 0.85 Pg C yr-1). The rate of prokaryotic biomass decline is one-third that of zooplankton and fish, while the rate of increase in prokaryotic respiration is double. This suggests that future, warmer oceans could be increasingly dominated by prokaryotes, diverting a growing proportion of primary production into microbial food webs and away from higher trophic levels as well as reducing the capacity of the deep ocean to sequester carbon, all else being equal.

The immune modules conserved across the tree of life: Towards a definition of ancestral immunity.

Immune defence mechanisms exist across the tree of life in such diversity that prokaryotic antiviral responses have historically been considered unrelated to eukaryotic immunity. Mechanisms of defence in divergent eukaryotes were similarly believed to be largely clade specific. However, recent data indicate that a subset of modules (domains and proteins) from prokaryote defence systems are conserved in eukaryotes and populate many stages of innate immune pathways. In this Essay, we propose the notion of ancestral immunity, which corresponds to the set of immune modules conserved between prokaryotes and eukaryotes. After offering a typology of ancestral immunity, we speculate on the selective pressures that could have led to the differential conservation of specific immune modules across domains of life. The exploration of ancestral immunity is in its infancy and appears full of promises to illuminate immune evolution, and also to identify and decipher immune mechanisms of economic, ecological, and therapeutic importance.

Quantifying functional redundancy in polysaccharide-degrading prokaryotic communities.

BACKGROUND: Functional redundancy (FR) is widely present, but there is no consensus on its formation process and influencing factors. Taxonomically distinct microorganisms possessing genes for the same function in a community lead to within-community FR, and distinct assemblies of microorganisms in different communities playing the same functional roles are termed between-community FR. We proposed two formulas to respectively quantify the degree of functional redundancy within and between communities and analyzed the FR degrees of carbohydrate degradation functions in global environment samples using the genetic information of glycoside hydrolases (GHs) encoded by prokaryotes. RESULTS: Our results revealed that GHs are each encoded by multiple taxonomically distinct prokaryotes within a community, and the enzyme-encoding prokaryotes are further distinct between almost any community pairs. The within- and between-FR degrees are primarily affected by the alpha and beta community diversities, respectively, and are also affected by environmental factors (e.g., pH, temperature, and salinity). The FR degree of the prokaryotic community is determined by deterministic factors. CONCLUSIONS: We conclude that the functional redundancy of GHs is a stabilized community characteristic. This study helps to determine the FR formation process and influencing factors and provides new insights into the relationships between prokaryotic community biodiversity and ecosystem functions. Video Abstract.

Atomic Force Microscopy Imaging and Analysis of Prokaryotic Genome Organization.

This protocol describes the application of atomic force microscopy for structural analysis of prokaryotic and organellar nucleoids. It is based on a simple cell manipulation procedure that enables stepwise dissection of the nucleoid. The procedure includes (i) on-substrate lysis of cells and (ii) enzyme treatment, followed by atomic force microscopy. This type of dissection analysis permits analysis of nucleoid structure ranging from the fundamental units assembled on DNA to higher-order levels of organization. The combination with molecular-genetic and biochemical techniques further permits analysis of the functions of key nucleoid factors relevant to signal-induced structural reorganization or building up of basic structures, as seen for Dps in Escherichia coli and TrmBL2 in Thermococcus kodakarensis. These systems are described here as examples of the successful application of AFM for this purpose. Moreover, we describe the procedures needed for quantitative analysis of the data.

Biogeography and dynamics of prokaryotic and microeukaryotic community assembly across 2600 km in the coastal and shelf ecosystems of the China Seas.

Marine prokaryotes and microeukaryotes are essential components of microbial food webs, and drive the biogeochemical cycling. However, the underlying ecological mechanisms driving prokaryotic and microeukaryotic community assembly in large-scale coastal ecosystems remain unclear. In this study, we studied biogeographic patterns of prokaryotic and microeukaryotic communities in the coastal and shelf ecosystem of the China Seas. Results showed that prokaryotic richness was the highest in the Yangtze River Plume, whereas microeukaryotic richness decreased from south to north. Prokaryotic-microeukaryotic co-occurrence networks display greater complexity in the Yangtze River Plume compared to other regions, potentially indicating higher environmental heterogeneity. Furthermore, the cross-domain networks revealed that prokaryotes were more interconnected with each other than with microeukaryotes or between microeukaryotes, and all hub nodes were bacterial taxa, suggesting that prokaryotes may be more important for sustaining the stability and multifunctionality of coastal ecosystem than microeukaryotes. Variation Partitioning Analysis revealed that approximately equal proportions of environmental, biotic and spatial factors contribute to variations in microbial community composition. Temperature was the primary environmental driver of both prokaryotic and microeukaryotic communities across the China Seas. Additionally, stochastic processes (dispersal limitation) and deterministic processes (homogeneous selection) were two major ecological factors in shaping microeukaryotic and prokaryotic assemblages, respectively, suggesting their different environmental plasticity and evolutionary mechanisms. Overall, these results demonstrate both prokaryotic and microeukaryotic communities displayed a latitude-driven distribution pattern and different assembly mechanisms, improving our understanding of microbial biogeography patterns under global change and anthropogenic activity driven habitat diversification in the coastal and shelf ecosystem.

Internal carbon recycling by heterotrophic prokaryotes compensates for mismatches between phytoplankton production and heterotrophic consumption.

Molecular observational tools are useful for characterizing the composition and genetic endowment of microbial communities but cannot measure fluxes, which are critical for the understanding of ecosystems. To overcome these limitations, we used a mechanistic inference approach to estimate dissolved organic carbon (DOC) production and consumption by phytoplankton operational taxonomic units and heterotrophic prokaryotic amplicon sequence variants and inferred carbon fluxes between members of this microbial community from Western English Channel time-series data. Our analyses focused on phytoplankton spring and summer blooms, as well as bacteria summer blooms. In spring blooms, phytoplankton DOC production exceeds heterotrophic prokaryotic consumption, but in bacterial summer blooms heterotrophic prokaryotes consume three times more DOC than produced by the phytoplankton. This mismatch is compensated by heterotrophic prokaryotic DOC release by death, presumably from viral lysis. In both types of summer blooms, large amounts of the DOC liberated by heterotrophic prokaryotes are reused through internal recycling, with fluxes between different heterotrophic prokaryotes being at the same level as those between phytoplankton and heterotrophic prokaryotes. In context, internal recycling accounts for approximately 75% and 30% of the estimated net primary production (0.16 vs 0.22 and 0.08 vs 0.29 µmol l-1 d-1) in bacteria and phytoplankton summer blooms, respectively, and thus represents a major component of the Western English Channel carbon cycle. We have concluded that internal recycling compensates for mismatches between phytoplankton DOC production and heterotrophic prokaryotic consumption, and we encourage future analyses on aquatic carbon cycles to investigate fluxes between heterotrophic prokaryotes, specifically internal recycling.