Protein homology detection by HMM-HMM comparison

N4BP1 functions as a dimerization-dependent linear ubiquitin reader which regulates TNF signalling

Signalling through TNFR1 modulates proinflammatory gene transcription and programmed cell death, and its impairment causes autoimmune diseases and cancer. NEDD4-binding protein 1 (N4BP1) is a critical suppressor of proinflammatory cytokine production that acts as a regulator of innate immune signalling and inflammation. However, our current understanding about the molecular properties that enable N4BP1 to exert its suppressive potential remain limited. Here, we show that N4BP1 is a novel linear ubiquitin reader that negatively regulates NFκB signalling by its unique dimerization-dependent ubiquitin-binding module that we named LUBIN. Dimeric N4BP1 strategically positions two non-selective ubiquitin-binding domains to ensure preferential recognition of linear ubiquitin. Under proinflammatory conditions, N4BP1 is recruited to the nascent TNFR1 signalling complex, where it regulates duration of proinflammatory signalling in LUBIN-dependent manner. N4BP1 deficiency accelerates TNFα-induced cell death by increasing complex II assembly. Under proapoptotic conditions, caspase-8 mediates proteolytic processing of N4BP1, resulting in rapid degradation of N4BP1 by the 26 S proteasome, and acceleration of apoptosis. In summary, our findings demonstrate that N4BP1 dimerization creates a novel type of ubiquitin reader that selectively recognises linear ubiquitin which enables the timely and coordinated regulation of TNFR1-mediated inflammation and cell death.

The DBB Family in Populus trichocarpa: Identification, Characterization, Evolution and Expression Profiles

The B-box proteins (BBXs) encode a family of zinc-finger transcription factors that regulate the plant circadian rhythm and early light morphogenesis. The double B-box (DBB) family is in the class of the B-box family, which contains two conserved B-box domains and lacks a CCT (CO, CO-like and TOC1) motif. In this study, the identity, classification, structures, conserved motifs, chromosomal location, cis elements, duplication events, and expression profiles of the PtrDBB genes were analyzed in the woody model plant Populus trichocarpa. Here, 12 PtrDBB genes (PtrDBB1-PtrDBB12) were identified and classified into four distinct groups, and all of them were homogeneously spread among eight out of seventeen poplar chromosomes. The collinearity analysis of the DBB family genes from P. trichocarpa and two other species (Z. mays and A. thaliana) indicated that segmental duplication gene pairs and high-level conservation were identified. The analysis of duplication events demonstrates an insight into the evolutionary patterns of DBB genes. The previously published transcriptome data showed that PtrDBB genes represented distinct expression patterns in various tissues at different stages. In addition, it was speculated that several PtrDBBs are involved in the responsive to drought stress, light/dark, and ABA and MeJA treatments, which implied that they might function in abiotic stress and phytohormone responses. In summary, our results contribute to the further understanding of the DBB family and provide a reference for potential functional studies of PtrDBB genes in P. trichocarpa.

PLMSearch: Protein language model powers accurate and fast sequence search for remote homology

Homologous protein search is one of the most commonly used methods for protein annotation and analysis. Compared to structure search, detecting distant evolutionary relationships from sequences alone remains challenging. Here we propose PLMSearch (Protein Language Model), a homologous protein search method with only sequences as input. PLMSearch uses deep representations from a pre-trained protein language model and trains the similarity prediction model with a large number of real structure similarity. This enables PLMSearch to capture the remote homology information concealed behind the sequences. Extensive experimental results show that PLMSearch can search millions of query-target protein pairs in seconds like MMseqs2 while increasing the sensitivity by more than threefold, and is comparable to state-of-the-art structure search methods. In particular, unlike traditional sequence search methods, PLMSearch can recall most remote homology pairs with dissimilar sequences but similar structures. PLMSearch is freely available at https://dmiip.sjtu.edu.cn/PLMSearch .

Altruistic feeding and cell-cell signaling during bacterial differentiation actively enhance phenotypic heterogeneity

Starvation triggers bacterial spore formation, a committed differentiation program that transforms a vegetative cell into a dormant spore. Cells in a population enter sporulation non-uniformly to secure against the possibility that favorable growth conditions, which puts sporulation-committed cells at a disadvantage, may resume. This heterogeneous behavior is initiated by a passive mechanism: stochastic activation of a master transcriptional regulator. Here, we identify a cell-cell communication pathway that actively promotes phenotypic heterogeneity, wherein Bacillus subtilis cells that start sporulating early utilize a calcineurin-like phosphoesterase to release glycerol, which simultaneously acts as a signaling molecule and a nutrient to delay non-sporulating cells from entering sporulation. This produced a more diverse population that was better poised to exploit a sudden influx of nutrients compared to those generating heterogeneity via stochastic gene expression alone. Although conflict systems are prevalent among microbes, genetically encoded cooperative behavior in unicellular organisms can evidently also boost inclusive fitness.

Design, synthesis and preliminary biological evaluation of rivastigmine-INDY hybrids as multitarget ligands against Alzheimer's disease by targeting butyrylcholinesterase and DYRK1A/CLK1 kinases

Based on a multitarget approach implementing rivastigmine-INDY hybrids 1, we identified a set of pseudo-irreversible carbamate-type inhibitors of eqBuChE that, after carbamate transfer at the active site serine residue, released the corresponding INDY analogues 2 endowed with hDYRK1A/hCLK1 kinases inhibitory properties. A SAR study and molecular docking investigation of both series of compounds 1 and 2 revealed that appropriate structural modifications at the carbamate moiety and at the N-appendage of the benzothiazole core led to potent and selective eqBuChE inhibitors with IC50 up to 27 nM and potent hDYRK1A and hCLK1 inhibitors with IC50 up to 106 nM and 17 nM respectively. Pleasingly, identification of the matched pair of compounds 1b/2b with a good balance between inhibition of eqBuChE and hDYRK1A/hCLK1 kinases (IC50 = 68 nM and IC50 = 529/54 nM, respectively) further validated our multitarget approach based on a sequential mechanism of action. In addition, target compound 1b exhibited a suitable ADMET profile, including good brain permeability and high stability in PBS, encouraging further biological investigation as a drug candidate.

Discovery of cytosine deaminases enables base-resolution methylome mapping using a single enzyme

Deaminases have important uses in modification detection and genome editing. However, the range of applications is limited by the small number of characterized enzymes. To expand the toolkit of deaminases, we developed an in vitro approach that bypasses a major hurdle with their toxicity in cells. We assayed 175 putative cytosine deaminases on a variety of substrates and found a broad range of activity on double- and single-stranded DNA in various sequence contexts, including CpG-specific deaminases and enzymes without sequence preference. We also characterized enzyme selectivity across six DNA modifications and reported enzymes that do not deaminate modified cytosines. The detailed analysis of diverse deaminases opens new avenues for biotechnological and medical applications. As a demonstration, we developed SEM-seq, a non-destructive single-enzyme methylation sequencing method using a modification-sensitive double-stranded DNA deaminase. The streamlined protocol enables accurate, base-resolution methylome mapping of scarce biological material, including cell-free DNA and 10 pg input DNA.

Forty-nine metagenomic-assembled genomes from an aquatic virome expand Caudoviricetes by 45 potential new families and the newly uncovered Gossevirus of Bamfordvirae

Twenty complete genomes (29-63 kb) and 29 genomes with an estimated completeness of over 90 % (30-90 kb) were identified for novel dsDNA viruses in the Yangshan Harbor metavirome. These newly discovered viruses contribute to the expansion of viral taxonomy by introducing 46 potential new families. Except for one virus, all others belong to the class Caudoviricetes. The exception is a novel member of the recently characterized viral group known as Gossevirus. Fifteen viruses were predicted to be temperate. The predicted hosts for the viruses appear to be involved in various aspects of the nitrogen cycle, including nitrogen fixation, oxidation and denitrification. Two viruses were identified to have a host of Flavobacterium and Tepidimonas fonticaldi, respectively, by matching CRISPR spacers with viral protospacers. Our findings provide an overview for characterizing and identifying specific viruses from Yangshan Harbor. The Gossevirus-like virus uncovered emphasizes the need for further comprehensive isolation and investigation of polinton-like viruses.

Finding Highly Similar Regions of Genomic Sequences Through Homomorphic Encryption

Finding highly similar regions of genomic sequences is a basic computation of genomic analysis. Genomic analyses on a large amount of data are efficiently processed in cloud environments, but outsourcing them to a cloud raises concerns over the privacy and security issues. Homomorphic encryption (HE) is a powerful cryptographic primitive that preserves privacy of genomic data in various analyses processed in an untrusted cloud environment. We introduce an efficient algorithm for finding highly similar regions of two homomorphically encrypted sequences, and describe how to implement it using the bit-wise and word-wise HE schemes. In the experiment, our algorithm outperforms an existing algorithm by up to two orders of magnitude in terms of elapsed time. Overall, it finds highly similar regions of the sequences in real data sets in a feasible time.

Mriyaviruses: Small Relatives of Giant Viruses

The phylum Nucleocytoviricota consists of large and giant viruses that range in genome size from about 100 kilobases (kb) to more than 2.5 megabases. Here, using metagenome mining followed by extensive phylogenomic analysis and protein structure comparison, we delineate a distinct group of viruses with double-stranded (ds) DNA genomes in the range of 35-45 kb that appear to be related to the Nucleocytoviricota. In phylogenetic trees of the conserved double jelly-roll major capsid proteins (MCP) and DNA packaging ATPases, these viruses do not show affinity to any particular branch of the Nucleocytoviricota and accordingly would comprise a class which we propose to name "Mriyaviricetes" (after Ukrainian Mriya, dream). Structural comparison of the MCP suggests that, among the extant virus lineages, mriyaviruses are the closest one to the ancestor of the Nucleocytoviricota. In the phylogenetic trees, mriyaviruses split into two well-separated branches, the family Yaraviridae and proposed new family "Gamadviridae". The previously characterized members of these families, Yaravirus and Pleurochrysis sp. endemic viruses, infect amoeba and haptophytes, respectively. The genomes of the rest of the mriyaviruses were assembled from metagenomes from diverse environments, suggesting that mriyaviruses infect various unicellular eukaryotes. Mriyaviruses lack DNA polymerase, which is encoded by all other members of the Nucleocytoviricota, and RNA polymerase subunits encoded by all cytoplasmic viruses among the Nucleocytoviricota, suggesting that they replicate in the host cell nuclei. All mriyaviruses encode a HUH superfamily endonuclease that is likely to be essential for the initiation of virus DNA replication via the rolling circle mechanism.

Virus-prokaryote infection pairs associated with prokaryotic production in a freshwater lake

Viruses infect and kill prokaryotic populations in a density- or frequency-dependent manner and affect carbon cycling. However, the effects of the stratification transition, including the stratified and de-stratified periods, on the changes in prokaryotic and viral communities and their interactions remain unclear. We conducted a monthly survey of the surface and deep layers of a large and deep freshwater lake (Lake Biwa, Japan) for a year and analyzed the prokaryotic production and prokaryotic and viral community composition. Our analysis revealed that, in the surface layer, 19 prokaryotic species, accounting for approximately 40% of the total prokaryotic abundance, could potentially contribute to the majority of prokaryotic production, which is the highest during the summer and is suppressed by viruses. This suggests that a small fraction of prokaryotes and phages were the key infection pairs during the peak period of prokaryotic activity in the freshwater lake. We also found that approximately 50% of the dominant prokaryotic and viral species in the deep layer were present throughout the study period. This suggests that the "kill the winner" model could explain the viral impact on prokaryotes in the surface layer, but other dynamics may be at play in the deep layer. Furthermore, we found that annual vertical mixing could result in a similar rate of community change between the surface and deep layers. These findings may be valuable in understanding how communities and the interaction among them change when freshwater lake stratification is affected by global warming in the future.IMPORTANCEViral infection associated with prokaryotic production occurs in a density- or frequency-dependent manner and regulates the prokaryotic community. Stratification transition and annual vertical mixing in freshwater lakes are known to affect the prokaryotic community and the interaction between prokaryotes and viruses. By pairing measurements of virome analysis and prokaryotic production of a 1-year survey of the depths of surface and deep layers, we revealed (i) the prokaryotic infection pairs associated with prokaryotic production and (ii) the reset in prokaryotic and viral communities through annual vertical mixing in a freshwater lake. Our results provide a basis for future work into changes in stratification that may impact the biogeochemical cycling in freshwater lakes.

Recent Progress of Protein Tertiary Structure Prediction

The prediction of three-dimensional (3D) protein structure from amino acid sequences has stood as a significant challenge in computational and structural bioinformatics for decades. Recently, the widespread integration of artificial intelligence (AI) algorithms has substantially expedited advancements in protein structure prediction, yielding numerous significant milestones. In particular, the end-to-end deep learning method AlphaFold2 has facilitated the rise of structure prediction performance to new heights, regularly competitive with experimental structures in the 14th Critical Assessment of Protein Structure Prediction (CASP14). To provide a comprehensive understanding and guide future research in the field of protein structure prediction for researchers, this review describes various methodologies, assessments, and databases in protein structure prediction, including traditionally used protein structure prediction methods, such as template-based modeling (TBM) and template-free modeling (FM) approaches; recently developed deep learning-based methods, such as contact/distance-guided methods, end-to-end folding methods, and protein language model (PLM)-based methods; multi-domain protein structure prediction methods; the CASP experiments and related assessments; and the recently released AlphaFold Protein Structure Database (AlphaFold DB). We discuss their advantages, disadvantages, and application scopes, aiming to provide researchers with insights through which to understand the limitations, contexts, and effective selections of protein structure prediction methods in protein-related fields.

The structural basis for deubiquitination by the fingerless USP-type effector TssM

Intracellular bacteria are threatened by ubiquitin-mediated autophagy, whenever the bacterial surface or enclosing membrane structures become targets of host ubiquitin ligases. As a countermeasure, many intracellular pathogens encode deubiquitinase (DUB) effectors to keep their surfaces free of ubiquitin. Most bacterial DUBs belong to the OTU or CE-clan families. The betaproteobacteria Burkholderia pseudomallei and Burkholderia mallei, causative agents of melioidosis and glanders, respectively, encode the TssM effector, the only known bacterial DUB belonging to the USP class. TssM is much shorter than typical eukaryotic USP enzymes and lacks the canonical ubiquitin-recognition region. By solving the crystal structures of isolated TssM and its complex with ubiquitin, we found that TssM lacks the entire "Fingers" subdomain of the USP fold. Instead, the TssM family has evolved the functionally analog "Littlefinger" loop, which is located towards the end of the USP domain and recognizes different ubiquitin interfaces than those used by USPs. The structures revealed the presence of an N-terminal immunoglobulin-fold domain, which is able to form a strand-exchange dimer and might mediate TssM localization to the bacterial surface.

WarA, a remote homolog of NpmA and KamB from Nocardia wallacei, confers broad spectrum aminoglycoside resistance in Nocardia and Mycobacteria

OBJECTIVES

Aminoglycoside resistance in bacteria is typically conferred by specific drug-modifying enzymes. Infrequently, such resistance is achieved through 16S ribosomal RNA methyltransferases, such as NpmA and KamB encoded by Escherichia coli and Streptoalloteichus tenebrarius, respectively. These enzymes are not widespread and have not been described in Nocardia species to date.

METHODS

We report the genomic mining of 18 Nocardia wallacei isolates that were found to be specifically and substantially resistant to amikacin.

RESULTS

We identified a gene coding for a protein with very distant homology to NpmA and KamB. However, 3-D modeling revealed that the tertiary structure of these three proteins was highly similar. Cloning and expressing this gene in two susceptible bacteria Nocardia asteroides, and Mycobacterium smegmatis (another Actinobacterium) led to high-level, pan-aminoglycoside resistance in both cases. We named this gene warA (Wallacei Amikacin Resistance A).

CONCLUSIONS

This is the first description and experimental characterization of a gene of this family in Nocardia, and the first demonstration that such activity could lead to pan-aminoglycoside resistance in Mycobacteria as well. The discovery of this novel gene has important biotechnology and clinical implications.

Hiding in plain sight: The discovery of complete genomes of 11 hypothetical spindle-shaped viruses that putatively infect mesophilic ammonia-oxidizing archaea

The genome of a putative Nitrosopumilaceae virus with a hypothetical spindle-shaped particle morphology was identified in the Yangshan Harbour metavirome from the East China Sea through protein similarity comparison and structure analysis. This discovery was accompanied by a set of 10 geographically dispersed close relatives found in the environmental virus datasets from typical locations of ammonia-oxidizing archaeon distribution. Its host prediction was supported by iPHoP prediction and protein sequence similarity. The structure of the predicted major capsid protein, together with the overall N-glycosylation site, the transmembrane helices prediction, the hydrophilicity profile, and the docking simulation of the major capsid proteins, indicate that these viruses resemble spindle-shaped viruses. It suggests a similarly assembled structure and, consequently, a possibly spindle-shaped morphology of these newly discovered archaeal viruses.

Catalytic activity of the Bin3/MePCE methyltransferase domain is dispensable for 7SK snRNP function in Drosophila melanogaster

Methylphosphate Capping Enzyme (MePCE) monomethylates the gamma phosphate at the 5' end of the 7SK noncoding RNA, a modification thought to protect 7SK from degradation. 7SK serves as a scaffold for assembly of a snRNP complex that inhibits transcription by sequestering the positive elongation factor P-TEFb. While much is known about the biochemical activity of MePCE in vitro, little is known about its functions in vivo, or what roles-if any-there are for regions outside the conserved methyltransferase domain. Here, we investigated the role of Bin3, the Drosophila ortholog of MePCE, and its conserved functional domains in Drosophila development. We found that bin3 mutant females had strongly reduced rates of egg-laying, which was rescued by genetic reduction of P-TEFb activity, suggesting that Bin3 promotes fecundity by repressing P-TEFb. bin3 mutants also exhibited neuromuscular defects, analogous to a patient with MePCE haploinsufficiency. These defects were also rescued by genetic reduction of P-TEFb activity, suggesting that Bin3 and MePCE have conserved roles in promoting neuromuscular function by repressing P-TEFb. Unexpectedly, we found that a Bin3 catalytic mutant (Bin3Y795A) could still bind and stabilize 7SK and rescue all bin3 mutant phenotypes, indicating that Bin3 catalytic activity is dispensable for 7SK stability and snRNP function in vivo. Finally, we identified a metazoan-specific motif (MSM) outside of the methyltransferase domain and generated mutant flies lacking this motif (Bin3ΔMSM). Bin3ΔMSM mutant flies exhibited some-but not all-bin3 mutant phenotypes, suggesting that the MSM is required for a 7SK-independent, tissue-specific function of Bin3.

CRISPR-Cas-based identification of a sialylated human milk oligosaccharides utilization cluster in the infant gut commensal Bacteroides dorei

The infant gut microbiome is impacted by early-life feeding, as human milk oligosaccharides (HMOs) found in breastmilk cannot be digested by infants and serve as nutrients for their gut bacteria. While the vast majority of HMO-utilization research has focused on Bifidobacterium species, recent studies have suggested additional HMO-utilizers, mostly Bacteroides, yet their utilization mechanism is poorly characterized. Here, we investigate Bacteroides dorei isolates from breastfed-infants and identify that polysaccharide utilization locus (PUL) 33 enables B. dorei to utilize sialylated HMOs. We perform transcriptional profiling and identity upregulated genes when growing on sialylated HMOs. Using CRISPR-Cas12 to knock-out four PUL33 genes, combined with complementation assays, we identify GH33 as the critical gene in PUL33 for sialylated HMO-utilization. This demonstration of an HMO-utilization system by Bacteroides species isolated from infants opens the way to further characterization of additional such systems, to better understand HMO-utilization in the infant gut.

PLAT domain protein 1 (PLAT1/PLAFP) binds to the Arabidopsis thaliana plasma membrane and inserts a lipid

Robust agricultural yields depend on the plant's ability to fix carbon amid variable environmental conditions. Over seasonal and diurnal cycles, the plant must constantly adjust its metabolism according to available resources or external stressors. The metabolic changes that a plant undergoes in response to stress are well understood, but the long-distance signaling mechanisms that facilitate communication throughout the plant are less studied. The phloem is considered the predominant conduit for the bidirectional transport of these signals in the form of metabolites, nucleic acids, proteins, and lipids. Lipid trafficking through the phloem in particular attracted our attention due to its reliance on soluble lipid-binding proteins (LBP) that generate and solubilize otherwise membrane-associated lipids. The Phloem Lipid-Associated Family Protein (PLAFP) from Arabidopsis thaliana is generated in response to abiotic stress as is its lipid-ligand phosphatidic acid (PA). PLAFP is proposed to transport PA through the phloem in response to drought stress. To understand the interactions between PLAFP and PA, nearly 100 independent systems comprised of the protein and one PA, or a plasma membrane containing varying amounts of PA, were simulated using atomistic classical molecular dynamics methods. In these simulations, PLAFP is found to bind to plant plasma membrane models independent of the PA concentration. When bound to the membrane, PLAFP adopts a binding pose where W41 and R82 penetrate the membrane surface and anchor PLAFP. This triggers a separation of the two loop regions containing W41 and R82. Subsequent simulations indicate that PA insert into the β-sandwich of PLAFP, driven by interactions with multiple amino acids besides the W41 and R82 identified during the insertion process. Fine-tuning the protein-membrane and protein-PA interface by mutating a selection of these amino acids may facilitate engineering plant signaling processes by modulating the binding response.

Variants in exon 2 of MED12 gene causes uterine leiomyoma's through over-expression of MMP-9 of ECM pathway

AIMS

To study the impact of Mediator complex subunit 12 (MED12) gene variants on the encoded protein's function and pathogenic relevance for genesis of uterine leiomyoma's (ULs).

METHODS

Mutational analysis in exon-2 of MED12 gene was performed by PCR amplification and DNA sequencing in 89 clinically diagnosed ULs tissues. Pathogenicity prediction of variation was performed by computational analysis. The functional effects of missense variation were done by quantity RT-PCR and western blot analysis.

RESULT(S)

Out of 89 samples, 40 (44.94%) had missense variation in 14 different CDS position of exon-2 of MED12 gene. Out of 40 missense variation, codon 44 had 25 (62.5%) looking as a hotspot region for mutation for ULs, because CDS position c130 and c131present at codon 44 that have necleotide change G>A, T, C at c130 and c131 have necleotide change G>A and C. We also find somenovel somatic mutations oncodon 36 (T > C), 38 (G>T) of exon-2 and 88 (G>C) of intron-2. No mutations were detected in uterine myometrium samples. Our computational analysis suggests that change in Med12c .131 G>A leads to single substitution of amino acid [Glycine (G) to Aspartate (D)] which has a pathogenic and lethal impact and may cause instability of MED12 protein. Further, analysis of extracellular matrix (ECM) component (MMP-2 & 9, COL4A2 and α-SMA) mRNA and protein expression levels in the set of ULs having MED12 mutation showed significantly higher expression of MMP-9 and α-SMA.

CONCLUSION(S)

The findings of present study suggest that missense variation in codon 44 of MED12 gene lead to the genesis of leiomyoma's through over-expression of MMP-9 of ECM pathway which could be therapeutically targeted for non-surgical management of ULs.

Outer membrane β-barrel structure prediction through the lens of AlphaFold2

Most proteins found in the outer membrane of gram-negative bacteria share a common domain: the transmembrane β-barrel. These outer membrane β-barrels (OMBBs) occur in multiple sizes and different families with a wide range of functions evolved independently by amplification from a pool of homologous ancestral ββ-hairpins. This is part of the reason why predicting their three-dimensional (3D) structure, especially by homology modeling, is a major challenge. Recently, DeepMind's AlphaFold v2 (AF2) became the first structure prediction method to reach close-to-experimental atomic accuracy in CASP even for difficult targets. However, membrane proteins, especially OMBBs, were not abundant during their training, raising the question of how accurate the predictions are for these families. In this study, we assessed the performance of AF2 in the prediction of OMBBs and OMBB-like folds of various topologies using an in-house-developed tool for the analysis of OMBB 3D structures, and barrOs. In agreement with previous studies on other membrane protein classes, our results indicate that AF2 predicts transmembrane β-barrel structures at high accuracy independently of the use of templates, even for novel topologies absent from the training set. These results provide confidence on the models generated by AF2 and open the door to the structural elucidation of novel transmembrane β-barrel topologies identified in high-throughput OMBB annotation studies or designed de novo.

Bioinformatic Approach of B and T Cell Epitopes of PLD and CP40 Proteins of Corynebacterium pseudotuberculosis ovis Mexican Isolate 2J-L towards a Peptide-Based Vaccine

Mapping B and T cell epitopes constitutes an important action for peptide vaccine design. PLD and CP40 virulence factors of Corynebacterium pseudotuberculosis biovar ovis, a causal agent of Caseous Lymphadenitis, have been evaluated in a murine model as good candidates for vaccine development. Therefore, the goal of this work was to in silico analyze B and T cell epitopes of the PLD and CP40 proteins of a Mexican isolate of Corynebacterium pseudotuberculosis ovis. The Immune Epitope Data Base and Resource website was employed to predict the linear and conformational B-cell, T CD4+, and T CD8+ epitopes of PLD and CP40 proteins of Corynebacterium pseudotuberculosis ovis Mexican strain 2J-L. Fifty B cell epitopes for PLD 2J-L and forty-seven for CP40 2J-L were estimated. In addition, T CD4+ and CD8+ cell epitopes were predicted for PLD 2J-L (MHC I:16 epitopes, MHC II:10 epitopes) and CP40 2J-L (MHC I: 15 epitopes, MHC II: 13 epitopes). This study provides epitopes, paying particular attention to sequences selected by different predictor programs and overlap sequences as B and T cell epitopes. PLD 2J-L and CP40 2J-L protein epitopes may aid in the design of a promising peptide-based vaccine against Caseous Lymphadenitis in Mexico.

John P, Umen J. Identification and preliminary characterization of conserved uncharacterized proteins from Chlamydomonas reinhardtii, Arabidopsis thaliana, and Setaria viridis

The rapid accumulation of sequenced plant genomes in the past decade has outpaced the still difficult problem of genome-wide protein-coding gene annotation. A substantial fraction of protein-coding genes in all plant genomes are poorly annotated or unannotated and remain functionally uncharacterized. We identified unannotated proteins in three model organisms representing distinct branches of the green lineage (Viridiplantae): Arabidopsis thaliana (eudicot), Setaria viridis (monocot), and Chlamydomonas reinhardtii (Chlorophyte alga). Using similarity searching, we identified a subset of unannotated proteins that were conserved between these species and defined them as Deep Green proteins. Bioinformatic, genomic, and structural predictions were performed to begin classifying Deep Green genes and proteins. Compared to whole proteomes for each species, the Deep Green set was enriched for proteins with predicted chloroplast targeting signals predictive of photosynthetic or plastid functions, a result that was consistent with enrichment for daylight phase diurnal expression patterning. Structural predictions using AlphaFold and comparisons to known structures showed that a significant proportion of Deep Green proteins may possess novel folds. Though only available for three organisms, the Deep Green genes and proteins provide a starting resource of high-value targets for further investigation of potentially new protein structures and functions conserved across the green lineage.

The impact of AI-based modeling on the accuracy of protein assembly prediction: Insights from CASP15

In CASP15, 87 predictors submitted around 11 000 models on 41 assembly targets. The community demonstrated exceptional performance in overall fold and interface contact predictions, achieving an impressive success rate of 90% (compared to 31% in CASP14). This remarkable accomplishment is largely due to the incorporation of DeepMind's AF2-Multimer approach into custom-built prediction pipelines. To evaluate the added value of participating methods, we compared the community models to the baseline AF2-Multimer predictor. In over 1/3 of cases, the community models were superior to the baseline predictor. The main reasons for this improved performance were the use of custom-built multiple sequence alignments, optimized AF2-Multimer sampling, and the manual assembly of AF2-Multimer-built subcomplexes. The best three groups, in order, are Zheng, Venclovas, and Wallner. Zheng and Venclovas reached a 73.2% success rate over all (41) cases, while Wallner attained 69.4% success rate over 36 cases. Nonetheless, challenges remain in predicting structures with weak evolutionary signals, such as nanobody-antigen, antibody-antigen, and viral complexes. Expectedly, modeling large complexes also remains challenging due to their high memory compute demands. In addition to the assembly category, we assessed the accuracy of modeling interdomain interfaces in the tertiary structure prediction targets. Models on seven targets featuring 17 unique interfaces were analyzed. Best predictors achieved a 76.5% success rate, with the UM-TBM group being the leader. In the interdomain category, we observed that the predictors faced challenges, as in the case of the assembly category, when the evolutionary signal for a given domain pair was weak or the structure was large. Overall, CASP15 witnessed unprecedented improvement in interface modeling, reflecting the AI revolution seen in CASP14.

Mce1R of Mycobacterium tuberculosis prefers long-chain fatty acids as specific ligands: a computational study

The mce1 operon of Mycobacterium tuberculosis, which codes the Mce1 transporter, facilitates the transport of fatty acids. Fatty acids are one of the major sources for carbon and energy for the pathogen during its intracellular survival and pathogenicity. The mce1 operon is transcriptionally regulated by Mce1R, a VanR-type regulator, which could bind specific ligands and control the expression of the mce1 operon accordingly. This work reports computational identification of Mce1R-specific ligands. Initially by employing cavity similarity search algorithm by the ProBis server, the cavities of the proteins similar to that of Mce1R and the bound ligands were identified from which fatty acids were selected as the potential ligands. From the earlier-generated monomeric structure, the dimeric structure of Mce1R was then modeled by the GalaxyHomomer server and validated computationally to use in molecular docking and molecular dynamics simulation analysis. The fatty acid ligands were found to dock within the cavity of Mce1R and the docked complexes were subjected to molecular dynamics simulation to explore their stabilities and other dynamic properties. The data suggest that Mce1R preferably binds to long-chain fatty acids and undergoes distinct structural changes upon binding.

Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15

We report the results of the "UM-TBM" and "Zheng" groups in CASP15 for protein monomer and complex structure prediction. These prediction sets were obtained using the D-I-TASSER and DMFold-Multimer algorithms, respectively. For monomer structure prediction, D-I-TASSER introduced four new features during CASP15: (i) a multiple sequence alignment (MSA) generation protocol that combines multi-source MSA searching and a structural modeling-based MSA ranker; (ii) attention-network based spatial restraints; (iii) a multi-domain module containing domain partition and arrangement for domain-level templates and spatial restraints; (iv) an optimized I-TASSER-based folding simulation system for full-length model creation guided by a combination of deep learning restraints, threading alignments, and knowledge-based potentials. For 47 free modeling targets in CASP15, the final models predicted by D-I-TASSER showed average TM-score 19% higher than the standard AlphaFold2 program. We thus showed that traditional Monte Carlo-based folding simulations, when appropriately coupled with deep learning algorithms, can generate models with improved accuracy over end-to-end deep learning methods alone. For protein complex structure prediction, DMFold-Multimer generated models by integrating a new MSA generation algorithm (DeepMSA2) with the end-to-end modeling module from AlphaFold2-Multimer. For the 38 complex targets, DMFold-Multimer generated models with an average TM-score of 0.83 and Interface Contact Score of 0.60, both significantly higher than those of competing complex prediction tools. Our analyses on complexes highlighted the critical role played by MSA generating, ranking, and pairing in protein complex structure prediction. We also discuss future room for improvement in the areas of viral protein modeling and complex model ranking.

Designing a novel and combinatorial multi-antigenic epitope-based vaccine "MarVax" against Marburg virus-a reverse vaccinology and immunoinformatics approach

CONTEXT

Marburg virus (MARV) is a member of the Filoviridae family and causes Marburg virus disease (MVD) among humans and primates. With fatality rates going up to 88%, there is currently no commercialized cure or vaccine to combat the infection. The National Institute of Allergy and Infectious Diseases (NIAID) classified MARV as priority pathogen A, which presages the need for a vaccine candidate which can provide stable, long-term adaptive immunity. The surface glycoprotein (GP) and fusion protein (FP) mediate the adherence, fusion, and entry of the virus into the host cell via the TIM-I receptor. Being important antigenic determinants, studies reveal that GP and FP are prone to evolutionary mutations, underscoring the requirement of a vaccine construct capable of eliciting a robust and sustained immune response. In this computational study, a reverse vaccinology approach was employed to design a combinatorial vaccine from conserved and antigenic epitopes of essential viral proteins of MARV, namely GP, VP24, VP30, VP35, and VP40 along with an endogenous protein large polymerase (L).

METHODS

Epitopes for T-cell and B-cell were predicted using TepiTool and ElliPro, respectively. The surface-exposed TLRs like TLR2, TLR4, and TLR5 were used to screen high-binding affinity epitopes using the protein-peptide docking platform MdockPeP. The best binding epitopes were selected and assembled with linkers to design a recombinant multi-epitope vaccine construct which was then modeled in Robetta. The in silico biophysical and biochemical analyses of the recombinant vaccine were performed. The docking and MD simulation of the vaccine using WebGro and CABS-Flex against TLRs support the stable binding of vaccine candidates. A virtual immune simulation to check the immediate and long-term immunogenicity was carried out using the C-ImmSim server.

RESULTS

The biochemical characteristics and docking studies with MD simulation establish the recombinant protein vaccine construct MarVax as a stable, antigenic, and potent vaccine molecule. Immune simulation studies reveal 1-year passive immunity which needs to be validated by in vivo studies.

Ongoing shuffling of protein fragments diversifies core viral functions linked to interactions with bacterial hosts

Biological modularity enhances evolutionary adaptability. This principle is vividly exemplified by bacterial viruses (phages), which display extensive genomic modularity. Phage genomes are composed of independent functional modules that evolve separately and recombine in various configurations. While genomic modularity in phages has been extensively studied, less attention has been paid to protein modularity-proteins consisting of distinct building blocks that can evolve and recombine, enhancing functional and genetic diversity. Here, we use a set of 133,574 representative phage proteins and highly sensitive homology detection to capture instances of domain mosaicism, defined as fragment sharing between two otherwise unrelated proteins, and to understand its relationship with functional diversity in phage genomes. We discover that unrelated proteins from diverse functional classes frequently share homologous domains. This phenomenon is particularly pronounced within receptor-binding proteins, endolysins, and DNA polymerases. We also identify multiple instances of recent diversification via domain shuffling in receptor-binding proteins, neck passage structures, endolysins and some members of the core replication machinery, often transcending distant taxonomic and ecological boundaries. Our findings suggest that ongoing diversification via domain shuffling is reflective of a co-evolutionary arms race, driven by the need to overcome various bacterial resistance mechanisms against phages.

Common evolutionary origins of the bacterial glycyl tRNA synthetase and alanyl tRNA synthetase

Aminoacyl-tRNA synthetases (aaRSs) establish the genetic code. Each aaRS covalently links a given canonical amino acid to a cognate set of tRNA isoacceptors. Glycyl tRNA aminoacylation is unusual in that it is catalyzed by different aaRSs in different lineages of the Tree of Life. We have investigated the phylogenetic distribution and evolutionary history of bacterial glycyl tRNA synthetase (bacGlyRS). This enzyme is found in early diverging bacterial phyla such as Firmicutes, Acidobacteria, and Proteobacteria, but not in archaea or eukarya. We observe relationships between each of six domains of bacGlyRS and six domains of four different RNA-modifying proteins. Component domains of bacGlyRS show common ancestry with (i) the catalytic domain of class II tRNA synthetases; (ii) the HD domain of the bacterial RNase Y; (iii) the body and tail domains of the archaeal CCA-adding enzyme; (iv) the anti-codon binding domain of the arginyl tRNA synthetase; and (v) a previously unrecognized domain that we call ATL (Ancient tRNA latch). The ATL domain has been found thus far only in bacGlyRS and in the universal alanyl tRNA synthetase (uniAlaRS). Further, the catalytic domain of bacGlyRS is more closely related to the catalytic domain of uniAlaRS than to any other aminoacyl tRNA synthetase. The combined results suggest that the ATL and catalytic domains of these two enzymes are ancestral to bacGlyRS and uniAlaRS, which emerged from common protein ancestors by bricolage, stepwise accumulation of protein domains, before the last universal common ancestor of life.

Functional and structural diversity in deubiquitinases of the Chlamydia-like bacterium Simkania negevensis

Besides the regulation of many cellular pathways, ubiquitination is important for defense against invading pathogens. Some intracellular bacteria have evolved deubiquitinase (DUB) effector proteins, which interfere with the host ubiquitin system and help the pathogen to evade xenophagy and lysosomal degradation. Most intracellular bacteria encode one or two DUBs, which are often linkage-promiscuous or preferentially cleave K63-linked chains attached to bacteria or bacteria-containing vacuoles. By contrast, the respiratory pathogen Legionella pneumophila possesses a much larger number of DUB effectors, including a K6-specific enzyme belonging to the OTU family and an M1-specific DUB uniquely found in this bacterium. Here, we report that the opportunistic pathogen Simkania negevensis, which is unrelated to Legionella but has a similar lifestyle, encodes a similarly large number of DUBs, including M1- and K6-specific enzymes. Simkania DUBs are highly diverse and include DUB classes never before seen in bacteria. Interestingly, the M1- and K6-specific DUBs of Legionella and Simkania are unrelated, suggesting that their acquisition occurred independently. We characterize the DUB activity of eight Simkania-encoded enzymes belonging to five different DUB classes. We also provide a structural basis for the M1-specificity of a Simkania DUB, which most likely evolved from a eukaryotic otubain-like precursor.

Enhancing alphafold-multimer-based protein complex structure prediction with MULTICOM in CASP15

To enhance the AlphaFold-Multimer-based protein complex structure prediction, we developed a quaternary structure prediction system (MULTICOM) to improve the input fed to AlphaFold-Multimer and evaluate and refine its outputs. MULTICOM samples diverse multiple sequence alignments (MSAs) and templates for AlphaFold-Multimer to generate structural predictions by using both traditional sequence alignments and Foldseek-based structure alignments, ranks structural predictions through multiple complementary metrics, and refines the structural predictions via a Foldseek structure alignment-based refinement method. The MULTICOM system with different implementations was blindly tested in the assembly structure prediction in the 15th Critical Assessment of Techniques for Protein Structure Prediction (CASP15) in 2022 as both server and human predictors. MULTICOM_qa ranked 3rd among 26 CASP15 server predictors and MULTICOM_human ranked 7th among 87 CASP15 server and human predictors. The average TM-score of the first predictions submitted by MULTICOM_qa for CASP15 assembly targets is ~0.76, 5.3% higher than ~0.72 of the standard AlphaFold-Multimer. The average TM-score of the best of top 5 predictions submitted by MULTICOM_qa is ~0.80, about 8% higher than ~0.74 of the standard AlphaFold-Multimer. Moreover, the Foldseek Structure Alignment-based Multimer structure Generation (FSAMG) method outperforms the widely used sequence alignment-based multimer structure generation.

Explainable protein function annotation using local structure embeddings

The rapid expansion of protein sequence and structure databases has resulted in a significant number of proteins with ambiguous or unknown function. While advances in machine learning techniques hold great potential to fill this annotation gap, current methods for function prediction are unable to associate global function reliably to the specific residues responsible for that function. We address this issue by introducing PARSE (Protein Annotation by Residue-Specific Enrichment), a knowledge-based method which combines pre-trained embeddings of local structural environments with traditional statistical techniques to identify enriched functions with residue-level explainability. For the task of predicting the catalytic function of enzymes, PARSE achieves comparable or superior global performance to state-of-the-art machine learning methods (F1 score > 85%) while simultaneously annotating the specific residues involved in each function with much greater precision. Since it does not require supervised training, our method can make one-shot predictions for very rare functions and is not limited to a particular type of functional label (e.g. Enzyme Commission numbers or Gene Ontology codes). Finally, we leverage the AlphaFold Structure Database to perform functional annotation at a proteome scale. By applying PARSE to the dark proteome-predicted structures which cannot be classified into known structural families-we predict several novel bacterial metalloproteases. Each of these proteins shares a strongly conserved catalytic site despite highly divergent sequences and global folds, illustrating the value of local structure representations for new function discovery.

Bacterial cell surface nanoenvironment requires a specialized chaperone to activate a peptidoglycan biosynthetic enzyme

Bacillus subtilis spores are produced inside the cytosol of a mother cell. Spore surface assembly requires the SpoVK protein in the mother cell, but its function is unknown. Here, we report that SpoVK is a dedicated chaperone from a distinct higher-order clade of AAA+ ATPases that activates the peptidoglycan glycosyltransferase MurG during sporulation, even though MurG does not normally require activation by a chaperone during vegetative growth. MurG redeploys to the spore surface during sporulation, where we show that the local pH is reduced and propose that this change in cytosolic nanoenvironment necessitates a specific chaperone for proper MurG function. Further, we show that SpoVK participates in a developmental checkpoint in which improper spore surface assembly inactivates SpoVK, which leads to sporulation arrest. The AAA+ ATPase clade containing SpoVK includes other dedicated chaperones involved in secretion, cell-envelope biosynthesis, and carbohydrate metabolism, suggesting that such fine-tuning might be a widespread feature of different subcellular nanoenvironments.

Uncovering new families and folds in the natural protein universe

We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database1. These models cover nearly all proteins that are known, including those challenging to annotate for function or putative biological role using standard homology-based approaches. In this study, we examine the extent to which the AlphaFold database has structurally illuminated this 'dark matter' of the natural protein universe at high predicted accuracy. We further describe the protein diversity that these models cover as an annotated interactive sequence similarity network, accessible at https://uniprot3d.org/atlas/AFDB90v4 . By searching for novelties from sequence, structure and semantic perspectives, we uncovered the β-flower fold, added several protein families to Pfam database2 and experimentally demonstrated that one of these belongs to a new superfamily of translation-targeting toxin-antitoxin systems, TumE-TumA. This work underscores the value of large-scale efforts in identifying, annotating and prioritizing new protein families. By leveraging the recent deep learning revolution in protein bioinformatics, we can now shed light into uncharted areas of the protein universe at an unprecedented scale, paving the way to innovations in life sciences and biotechnology.

The phageome in normal and inflamed human skin

Dysbiosis of skin microbiota drives the progression of atopic dermatitis (AD). The contribution of bacteriophages to bacterial community compositions in normal and inflamed skin is unknown. Using shotgun metagenomics from skin swabs of healthy individuals and patients with AD, we found 13,586 potential viral contiguous DNA sequences, which could be combined into 164 putative viral genomes including 133 putative phages. The Shannon diversity index for the viral metagenome-assembled genomes (vMAGs) did not correlate with AD. In total, we identified 28 vMAGs that differed significantly between normal and AD skin. Quantitative polymerase chain reaction validation of three complete vMAGs revealed their independence from host bacterium abundance. Our data indicate that normal and inflamed skin harbor distinct phageomes and suggest a causative relationship between changing viral and bacterial communities as a driver of skin pathology.

The Impact of AI-Based Modeling on the Accuracy of Protein Assembly Prediction: Insights from CASP15

In CASP15, 87 predictors submitted around 11,000 models on 41 assembly targets. The community demonstrated exceptional performance in overall fold and interface contact prediction, achieving an impressive success rate of 90% (compared to 31% in CASP14). This remarkable accomplishment is largely due to the incorporation of DeepMind's AF2-Multimer approach into custom-built prediction pipelines. To evaluate the added value of participating methods, we compared the community models to the baseline AF2-Multimer predictor. In over 1/3 of cases the community models were superior to the baseline predictor. The main reasons for this improved performance were the use of custom-built multiple sequence alignments, optimized AF2-Multimer sampling, and the manual assembly of AF2-Multimer-built subcomplexes. The best three groups, in order, are Zheng, Venclovas and Wallner. Zheng and Venclovas reached a 73.2% success rate over all (41) cases, while Wallner attained 69.4% success rate over 36 cases. Nonetheless, challenges remain in predicting structures with weak evolutionary signals, such as nanobody-antigen, antibody-antigen, and viral complexes. Expectedly, modeling large complexes remains also challenging due to their high memory compute demands. In addition to the assembly category, we assessed the accuracy of modeling interdomain interfaces in the tertiary structure prediction targets. Models on seven targets featuring 17 unique interfaces were analyzed. Best predictors achieved the 76.5% success rate, with the UM-TBM group being the leader. In the interdomain category, we observed that the predictors faced challenges, as in the case of the assembly category, when the evolutionary signal for a given domain pair was weak or the structure was large. Overall, CASP15 witnessed unprecedented improvement in interface modeling, reflecting the AI revolution seen in CASP14.

Characterization of an archaeal virus-host system reveals massive genomic rearrangements in a laboratory strain

Halophilic archaea (haloarchaea) are known to exhibit multiple chromosomes, with one main chromosome and one or several smaller secondary chromosomes or megaplasmids. Halorubrum lacusprofundi, a model organism for studying cold adaptation, exhibits one secondary chromosome and one megaplasmid that include a large arsenal of virus defense mechanisms. We isolated a virus (Halorubrum tailed virus DL1, HRTV-DL1) infecting Hrr. lacusprofundi, and present an in-depth characterization of the virus and its interactions with Hrr. lacusprofundi. While studying virus-host interactions between Hrr. lacusprofundi and HRTV-DL1, we uncover that the strain in use (ACAM34_UNSW) lost the entire megaplasmid and about 38% of the secondary chromosome. The loss included the majority of virus defense mechanisms, making the strain sensitive to HRTV-DL1 infection, while the type strain (ACAM34_DSMZ) appears to prevent virus replication. Comparing infection of the type strain ACAM34_DSMZ with infection of the laboratory derived strain ACAM34_UNSW allowed us to identify host responses to virus infection that were only activated in ACAM34_UNSW upon the loss of virus defense mechanisms. We identify one of two S-layer proteins as primary receptor for HRTV-DL1 and conclude that the presence of two different S-layer proteins in one strain provides a strong advantage in the arms race with viruses. Additionally, we identify archaeal homologs to eukaryotic proteins potentially being involved in the defense against virus infection.

Plasmodium ARK2 and EB1 drive unconventional spindle dynamics, during chromosome segregation in sexual transmission stages

The Aurora family of kinases orchestrates chromosome segregation and cytokinesis during cell division, with precise spatiotemporal regulation of its catalytic activities by distinct protein scaffolds. Plasmodium spp., the causative agents of malaria, are unicellular eukaryotes with three unique and highly divergent aurora-related kinases (ARK1-3) that are essential for asexual cellular proliferation but lack most canonical scaffolds/activators. Here we investigate the role of ARK2 during sexual proliferation of the rodent malaria Plasmodium berghei, using a combination of super-resolution microscopy, mass spectrometry, and live-cell fluorescence imaging. We find that ARK2 is primarily located at spindle microtubules in the vicinity of kinetochores during both mitosis and meiosis. Interactomic and co-localisation studies reveal several putative ARK2-associated interactors including the microtubule-interacting protein EB1, together with MISFIT and Myosin-K, but no conserved eukaryotic scaffold proteins. Gene function studies indicate that ARK2 and EB1 are complementary in driving endomitotic division and thereby parasite transmission through the mosquito. This discovery underlines the flexibility of molecular networks to rewire and drive unconventional mechanisms of chromosome segregation in the malaria parasite.

Improving AlphaFold2-based protein tertiary structure prediction with MULTICOM in CASP15

Since the 14th Critical Assessment of Techniques for Protein Structure Prediction (CASP14), AlphaFold2 has become the standard method for protein tertiary structure prediction. One remaining challenge is to further improve its prediction. We developed a new version of the MULTICOM system to sample diverse multiple sequence alignments (MSAs) and structural templates to improve the input for AlphaFold2 to generate structural models. The models are then ranked by both the pairwise model similarity and AlphaFold2 self-reported model quality score. The top ranked models are refined by a novel structure alignment-based refinement method powered by Foldseek. Moreover, for a monomer target that is a subunit of a protein assembly (complex), MULTICOM integrates tertiary and quaternary structure predictions to account for tertiary structural changes induced by protein-protein interaction. The system participated in the tertiary structure prediction in 2022 CASP15 experiment. Our server predictor MULTICOM_refine ranked 3rd among 47 CASP15 server predictors and our human predictor MULTICOM ranked 7th among all 132 human and server predictors. The average GDT-TS score and TM-score of the first structural models that MULTICOM_refine predicted for 94 CASP15 domains are ~0.80 and ~0.92, 9.6% and 8.2% higher than ~0.73 and 0.85 of the standard AlphaFold2 predictor respectively.

Protein coopted from a phage restriction system dictates orthogonal cell division plane selection in Staphylococcus aureus

The spherical bacterium Staphylococcus aureus, a leading cause of nosocomial infections, undergoes binary fission by dividing in two alternating orthogonal planes, but the mechanism by which S. aureus correctly selects the next cell division plane is not known. To identify cell division placement factors, we performed a chemical genetic screen that revealed a gene which we termed pcdA. We show that PcdA is a member of the McrB family of AAA+ NTPases that has undergone structural changes and a concomitant functional shift from a restriction enzyme subunit to an early cell division protein. PcdA directly interacts with the tubulin-like central divisome component FtsZ and localizes to future cell division sites before membrane invagination initiates. This parallels the action of another McrB family protein, CTTNBP2, which stabilizes microtubules in animals. We show that PcdA also interacts with the structural protein DivIVA and propose that the DivIVA/PcdA complex recruits unpolymerized FtsZ to assemble along the proper cell division plane. Deletion of pcdA conferred abnormal, non-orthogonal division plane selection, increased sensitivity to cell wall-targeting antibiotics, and reduced virulence in a murine infection model. Targeting PcdA could therefore highlight a treatment strategy for combatting antibiotic-resistant strains of S. aureus.

Protons taken hostage: Dynamic H-bond networks of the pH-sensing GPR68

Proton-sensing G Protein Coupled Receptors (GPCRs) sense changes in the extracellular pH to effect cell signaling for cellular homeostasis. They tend to be overexpressed in solid tumors associated with acidic extracellular pH, and are of direct interest as drug targets. How proton-sensing GPCRs sense extracellular acidification and activate upon protonation change is important to understand, because it may guide the design of therapeutics. Lack of publicly available experimental structures make it challenging to discriminate between conflicting mechanisms proposed for proton-binding, as main roles have been assigned to either an extracellular histidine cluster or to an internal carboxylic triad. Here we present a protocol to derive and evaluate structural models of the proton-sensing GPR68. This approach integrates state-of-the-art homology modeling with microsecond-timescale atomistic simulations, and with a detailed assessment of the compatibility of the structural models with known structural features of class A GPCRs. To decipher structural elements of potential interest for protonation-coupled conformational changes of GPR68, we used the best-compatible model as a starting point for independent atomistic simulations of GPR68 with different protonation states, and graph computations to characterize the response of GPR68 to changes in protonation. We found that GPR68 hosts an extended hydrogen-bond network that inter-connects the extracellular histidine cluster to the internal carboxylic triad, and which can even reach groups at the cytoplasmic G-protein binding site. Taken together, results suggest that GPR68 relies on dynamic, hydrogen-bond networks to inter-connect extracellular and internal proton-binding sites, and to elicit conformational changes at the cytoplasmic G-protein binding site.

Long-Read Sequencing Reveals Extensive DNA Methylations in Human Gut Phagenome Contributed by Prevalently Phage-Encoded Methyltransferases

DNA methylation plays a crucial role in the survival of bacteriophages (phages), yet the understanding of their genome methylation remains limited. In this study, DNA methylation patterns are analyzed in 8848 metagenome-assembled high-quality phages from 104 fecal samples using single-molecule real-time sequencing. The results demonstrate that 97.60% of gut phages exhibit methylation, with certain factors correlating with methylation densities. Phages with higher methylation densities appear to have potential viability advantages. Strikingly, more than one-third of the phages possess their own DNA methyltransferases (MTases). Increased MTase copies are associated with higher genome methylation densities, specific methylation motifs, and elevated prevalence of certain phage groups. Notably, the majority of these MTases share close homology with those encoded by gut bacteria, suggesting their exchange during phage-bacterium interactions. Furthermore, these MTases can be employed to accurately predict phage-host relationships. Overall, the findings indicate the widespread utilization of DNA methylation by gut DNA phages as an evasion mechanism against host defense systems, with a substantial contribution from phage-encoded MTases.

Biocomputational characterisation of MBO_200107 protein of Mycobacterium tuberculosis variant caprae: a molecular docking and simulation study

The principal objective of this study was to delineate the potentiality of the MBO_200107 protein from the Mycobacterium tuberculosis variant caprae in cancer research. It is a cytoplasmic protein, comprised of a 354-long amino acid chain, alkaline, had a molecular weight of 39089.37 Da, an isoelectric point of 9.62 and a grand average of hydropathicity of -0.345. One of the functional domains was predicted as Gammaglutamylcyclotransferase (GGCT). Among tertiary structures, the Modeller and Phyre2 model satisfied all the quality parameters, though they are truncated; contrarily, the I-TASSER model is full length and contains the sequence for the GGCT domain, though it did not meet all the quality parameters. It also has significant sequence similarities (47.5% by EMBOSS Water and 72.4% by EMBOSS Matcher) with a human GGCT, and the conserved sequences are confined to the GGCT domain of the MBO_200107. According to molecular docking analyses, the protein has a binding affinity of -4.8 kcal/mol by Autodock Vina and -56.465 kcal/mol by HPEPDOCK to the human glutathione (GSH), an essential metabolite for GGCT metabolism. The Molecular dynamic simulation of the docked complex showed the binding efficiency of the GSH to MBO_200107 with a minimal structural alteration. The in silico findings mentioned above revealed that the protein could be used as a supplementary tool in cancer research, such as designing vaccines or drugs where the role of GGCT has been implicated. Further, we recommend fully characterising the protein and conducting essential in vitro and in vivo experiments to determine its detailed usefulness.Communicated by Ramaswamy H. Sarma.

Widespread CRISPR-derived RNA regulatory elements in CRISPR-Cas systems

CRISPR-cas loci typically contain CRISPR arrays with unique spacers separating direct repeats. Spacers along with portions of adjacent repeats are transcribed and processed into CRISPR(cr) RNAs that target complementary sequences (protospacers) in mobile genetic elements, resulting in cleavage of the target DNA or RNA. Additional, standalone repeats in some CRISPR-cas loci produce distinct cr-like RNAs implicated in regulatory or other functions. We developed a computational pipeline to systematically predict crRNA-like elements by scanning for standalone repeat sequences that are conserved in closely related CRISPR-cas loci. Numerous crRNA-like elements were detected in diverse CRISPR-Cas systems, mostly, of type I, but also subtype V-A. Standalone repeats often form mini-arrays containing two repeat-like sequence separated by a spacer that is partially complementary to promoter regions of cas genes, in particular cas8, or cargo genes located within CRISPR-Cas loci, such as toxins-antitoxins. We show experimentally that a mini-array from a type I-F1 CRISPR-Cas system functions as a regulatory guide. We also identified mini-arrays in bacteriophages that could abrogate CRISPR immunity by inhibiting effector expression. Thus, recruitment of CRISPR effectors for regulatory functions via spacers with partial complementarity to the target is a common feature of diverse CRISPR-Cas systems.

Updated protein domain annotation of the PARP protein family sheds new light on biological function

AlphaFold2 and related computational tools have greatly aided studies of structural biology through their ability to accurately predict protein structures. In the present work, we explored AF2 structural models of the 17 canonical members of the human PARP protein family and supplemented this analysis with new experiments and an overview of recent published data. PARP proteins are typically involved in the modification of proteins and nucleic acids through mono or poly(ADP-ribosyl)ation, but this function can be modulated by the presence of various auxiliary protein domains. Our analysis provides a comprehensive view of the structured domains and long intrinsically disordered regions within human PARPs, offering a revised basis for understanding the function of these proteins. Among other functional insights, the study provides a model of PARP1 domain dynamics in the DNA-free and DNA-bound states and enhances the connection between ADP-ribosylation and RNA biology and between ADP-ribosylation and ubiquitin-like modifications by predicting putative RNA-binding domains and E2-related RWD domains in certain PARPs. In line with the bioinformatic analysis, we demonstrate for the first time PARP14's RNA-binding capability and RNA ADP-ribosylation activity in vitro. While our insights align with existing experimental data and are probably accurate, they need further validation through experiments.

Mechanistic and evolutionary insights into a type V-M CRISPR-Cas effector enzyme

RNA-guided type V CRISPR-Cas12 effectors provide adaptive immunity against mobile genetic elements (MGEs) in bacteria and archaea. Among diverse Cas12 enzymes, the recently identified Cas12m2 (CRISPR-Cas type V-M) is highly compact and has a unique RuvC active site. Although the non-canonical RuvC triad does not permit dsDNA cleavage, Cas12m2 still protects against invading MGEs through transcriptional silencing by strong DNA binding. However, the molecular mechanism of RNA-guided genome inactivation by Cas12m2 remains unknown. Here we report cryo-electron microscopy structures of two states of Cas12m2-CRISPR RNA (crRNA)-target DNA ternary complexes and the Cas12m2-crRNA binary complex, revealing structural dynamics during crRNA-target DNA heteroduplex formation. The structures indicate that the non-target DNA strand is tightly bound to a unique arginine-rich cluster in the recognition (REC) domains and the non-canonical active site in the RuvC domain, ensuring strong DNA-binding affinity of Cas12m2. Furthermore, a structural comparison of Cas12m2 with TnpB, a putative ancestor of Cas12 enzymes, suggests that the interaction of the characteristic coiled-coil REC2 insertion with the protospacer-adjacent motif-distal region of the heteroduplex is crucial for Cas12m2 to engage in adaptive immunity. Collectively, our findings improve mechanistic understanding of diverse type V CRISPR-Cas effectors and provide insights into the evolution of TnpB to Cas12 enzymes.

Microbiota present in combined endodontic-periodontal diseases and its risks for endocarditis

INTRODUCTION

Infective endocarditis (IE) is an inflammatory disease usually caused by bacteria that enter the bloodstream and establish infections in the inner linings or valves of the heart, including blood vessels. Despite the availability of modern antimicrobial and surgical treatments, IE continues to cause substantial morbidity and mortality. Oral microbiota is considered one of the most significant risk factors for IE. The objective of this study was to evaluate the microbiota present in root canal (RC) and periodontal pocket (PP) clinical samples in cases with combined endo-periodontal lesions (EPL) to detect species related to IE using NGS.

METHODS

Microbial samples were collected from 15 RCs and their associated PPs, also from 05 RCs with vital pulp tissues (negative control, NC). Genomic studies associated with bioinformatics, combined with structuring of a database (genetic sequences of bacteria reported for infective endocarditis), allowed for the assessment of the microbial community at both sites. Functional prediction was conducted using PICRUSt2.

RESULTS

Parvimonas, Streptococcus, and Enterococcus were the major genera detected in the RCs and PPs. A total of 79, 96, and 11 species were identified in the RCs, PPs, and NCs, respectively. From them, a total of 34 species from RCs, 53 from PPs, and 2 from NCs were related to IE. Functional inference demonstrated that CR and PP microbiological profiles may not be the only risk factors for IE but may also be associated with systemic diseases, including myocarditis, human cytomegalovirus infection, bacterial invasion of epithelial cells, Huntington's disease, amyotrophic lateral sclerosis, and hypertrophic cardiomyopathy. Additionally, it was possible to predict antimicrobial resistance variants for broad-spectrum drugs, including ampicillin, tetracycline, and macrolides.

CONCLUSION

Microorganisms present in the combined EPL may not be the only risk factor for IE but also for systemic diseases. Antimicrobial resistance variants for broad-spectrum drugs were inferred based on PICRUSt-2. State-of-the-art sequencing combined with bioinformatics has proven to be a powerful tool for conducting studies on microbial communities and could considerably assist in the diagnosis of serious infections.

CLINICAL RELEVANCE

Few studies have investigated the microbiota in teeth compromised by combined endo-periodontal lesions (EPL), but none have correlated the microbiological findings to any systemic condition, particularly IE, using NGS techniques. In such cases, the presence of apical periodontitis and periodontal disease can increase IE risk in susceptible patients.

Petascale Homology Search for Structure Prediction

The recent CASP15 competition highlighted the critical role of multiple sequence alignments (MSAs) in protein structure prediction, as demonstrated by the success of the top AlphaFold2-based prediction methods. To push the boundaries of MSA utilization, we conducted a petabase-scale search of the Sequence Read Archive (SRA), resulting in gigabytes of aligned homologs for CASP15 targets. These were merged with default MSAs produced by ColabFold-search and provided to ColabFold-predict. By using SRA data, we achieved highly accurate predictions (GDT_TS > 70) for 66% of the non-easy targets, whereas using ColabFold-search default MSAs scored highly in only 52%. Next, we tested the effect of deep homology search and ColabFold's advanced features, such as more recycles, on prediction accuracy. While SRA homologs were most significant for improving ColabFold's CASP15 ranking from 11th to 3rd place, other strategies contributed too. We analyze these in the context of existing strategies to improve prediction.

The G2-Like gene family in Populus trichocarpa: identification, evolution and expression profiles

The Golden2-like (GLK) transcription factors are plant-specific transcription factors (TFs) that perform extensive and significant roles in regulating chloroplast development. Here, genome-wide identification, classification, conserved motifs, cis-elements, chromosomal locations, evolution and expression patterns of the PtGLK genes in the woody model plant Populus trichocarpa were analyzed in detail. In total, 55 putative PtGLKs (PtGLK1-PtGLK55) were identified and divided into 11 distinct subfamilies according to the gene structure, motif composition and phylogenetic analysis. Synteny analysis showed that 22 orthologous pairs and highly conservation between regions of GLK genes across P. trichocarpa and Arabidopsis were identified. Furthermore, analysis of the duplication events and divergence times provided insight into the evolutionary patterns of GLK genes. The previously published transcriptome data indicated that PtGLK genes exhibited distinct expression patterns in various tissues and different stages. Additionally, several PtGLKs were significantly upregulated under the responses of cold stress, osmotic stress, and methyl jasmonate (MeJA) and gibberellic acid (GA) treatments, implying that they might take part in abiotic stress and phytohormone responses. Overall, our results provide comprehensive information on the PtGLK gene family and elucidate the potential functional characterization of PtGLK genes in P. trichocarpa.

BioSeq-Diabolo: Biological sequence similarity analysis using Diabolo

As the key for biological sequence structure and function prediction, disease diagnosis and treatment, biological sequence similarity analysis has attracted more and more attentions. However, the exiting computational methods failed to accurately analyse the biological sequence similarities because of the various data types (DNA, RNA, protein, disease, etc) and their low sequence similarities (remote homology). Therefore, new concepts and techniques are desired to solve this challenging problem. Biological sequences (DNA, RNA and protein sequences) can be considered as the sentences of "the book of life", and their similarities can be considered as the biological language semantics (BLS). In this study, we are seeking the semantics analysis techniques derived from the natural language processing (NLP) to comprehensively and accurately analyse the biological sequence similarities. 27 semantics analysis methods derived from NLP were introduced to analyse biological sequence similarities, bringing new concepts and techniques to biological sequence similarity analysis. Experimental results show that these semantics analysis methods are able to facilitate the development of protein remote homology detection, circRNA-disease associations identification and protein function annotation, achieving better performance than the other state-of-the-art predictors in the related fields. Based on these semantics analysis methods, a platform called BioSeq-Diabolo has been constructed, which is named after a popular traditional sport in China. The users only need to input the embeddings of the biological sequence data. BioSeq-Diabolo will intelligently identify the task, and then accurately analyse the biological sequence similarities based on biological language semantics. BioSeq-Diabolo will integrate different biological sequence similarities in a supervised manner by using Learning to Rank (LTR), and the performance of the constructed methods will be evaluated and analysed so as to recommend the best methods for the users. The web server and stand-alone package of BioSeq-Diabolo can be accessed at http://bliulab.net/BioSeq-Diabolo/server/.

Catalytic activity of the Bin3/MEPCE methyltransferase domain is dispensable for 7SK snRNP function in Drosophila melanogaster

Methylphosphate Capping Enzyme (MEPCE) monomethylates the gamma phosphate at the 5' end of the 7SK noncoding RNA, a modification thought to protect 7SK from degradation. 7SK serves as a scaffold for assembly of a snRNP complex that inhibits transcription by sequestering the positive elongation factor P-TEFb. While much is known about the biochemical activity of MEPCE in vitro, little is known about its functions in vivo, or what roles- if any-there are for regions outside the conserved methyltransferase domain. Here, we investigated the role of Bin3, the Drosophila ortholog of MEPCE, and its conserved functional domains in Drosophila development. We found that bin3 mutant females had strongly reduced rates of egg-laying, which was rescued by genetic reduction of P-TEFb activity, suggesting that Bin3 promotes fecundity by repressing P-TEFb. bin3 mutants also exhibited neuromuscular defects, analogous to a patient with MEPCE haploinsufficiency. These defects were also rescued by genetic reduction of P-TEFb activity, suggesting that Bin3 and MEPCE have conserved roles in promoting neuromuscular function by repressing P-TEFb. Unexpectedly, we found that a Bin3 catalytic mutant (Bin3Y795A) could still bind and stabilize 7SK and rescue all bin3 mutant phenotypes, indicating that Bin3 catalytic activity is dispensable for 7SK stability and snRNP function in vivo. Finally, we identified a metazoan-specific motif (MSM) outside of the methyltransferase domain and generated mutant flies lacking this motif (Bin3ΔMSM). Bin3ΔMSM mutant flies exhibited some-but not all-bin3 mutant phenotypes, suggesting that the MSM is required for a 7SK-independent, tissue-specific function of Bin3.

A DNA-PK phosphorylation site on MET regulates its signaling interface with the DNA damage response

The DNA damage response (DDR) is intertwined with signaling pathways downstream of oncogenic receptor tyrosine kinases (RTKs). To drive research into the application of targeted therapies as radiosensitizers, a better understanding of this molecular crosstalk is necessary. We present here the characterization of a previously unreported MET RTK phosphosite, Serine 1016 (S1016) that represents a potential DDR-MET interface. MET S1016 phosphorylation increases in response to irradiation and is mainly targeted by DNA-dependent protein kinase (DNA-PK). Phosphoproteomics unveils an impact of the S1016A substitution on the overall long-term cell cycle regulation following DNA damage. Accordingly, the abrogation of this phosphosite strongly perturbs the phosphorylation of proteins involved in the cell cycle and formation of the mitotic spindle, enabling cells to bypass a G2 arrest upon irradiation and leading to the entry into mitosis despite compromised genome integrity. This results in the formation of abnormal mitotic spindles and a lower proliferation rate. Altogether, the current data uncover a novel signaling mechanism through which the DDR uses a growth factor receptor system for regulating and maintaining genome stability.