Positive Interactions Between Lactic Acid Bacteria Could Be Mediated by Peptides Containing Branched-Chain Amino Acids

Lactic acid bacteria (LAB) are responsible for the sanitary, organoleptic, and health properties of most fermented products. Positive interactions between pairs of LAB strains, based on nitrogen dependencies, were previously demonstrated. In a chemically defined medium, using milk and lupin proteins as sole nitrogen source, two proteolytic strains were able to sustain the growth of non-proteolytic strains, but one did not. The objective of the present study was, thus, to determine which specific peptides were implicated in the positive interactions observed. Peptides produced and involved in the bacterial interactions were quantified using tandem mass spectrometry (LC-MS/MS). About 2,000 different oligopeptides ranging from 6 to more than 50 amino acids in length were identified during the time-course of the experiment. We performed a clustering approach to decipher the differences in peptide production during fermentation by the three proteolytic strains tested. We also performed sequence alignments on parental proteins and identified the cleavage site profiles of the three bacterial strains. Then, we characterized the peptides that were used by the non-proteolytic strains in monocultures. Hydrophobic and branched-chain amino acids within peptides were identified as essential in the interactions. Ultimately, better understanding how LAB can positively interact could be useful in multiple food-related fields, e.g., production of fermented food products with enhanced functional properties, or fermentation of new food matrices.

Characterization of Subtilosin Gene In Wild Type Bacillus Spp. And Possible Physiological Role

In a designed study to screen for antimicrobial exhibiting bacteria using molecular aspects, Bacillus species were considered to investigate antibiotic biosynthesis genes. 28 bacterial strains and 3 induced mutants were screened for the presence of subtilosin gene (sbo) and subtilosin through PCR and Mass spectrometry respectively. Sbo gene was detected in 16 out of 28 Bacillus strains. The results from gene sequences deliberated by multiple sequence alignments revealed high-level homology to the sequences of the sbo-alb gene locus of B. subtilis 168 and the other limited reported strains. Hence, this report provided additional strains to support the idea of subtilosin gene predominance amongst Bacillus strains isolated from environment and to find different species containing homologous genes, furthermore the utilization of its conserved region as a means of identifying Bacillus spp. that produce subtilosin. This is the first report to confirm the detection of subtilosin production from B. amyloliquefaciens.

Genetic variability and population structure of Leucinodes orbonalis (Guenée), a severe insect pest of brinjal in India

Aim: The present study was undertaken to provide valuable insights regarding population genetic structure of Leucinodes orbonalis from diverse agro-ecologies of India. Methodology: Molecular characterization of L. orbonalis populations collected from five major agro-climatic zones of India was carried out using mitochondrial cytochrome oxidase I (COI) gene. Collected specimens were subjected to DNA extractions, partial PCR amplification and sequencing of the target gene, and multiple sequence alignments. Results: The results showed very less diversity in the nucleotide positions of the COI sequences of 79 studied specimens, with a low number of segregating sites (30), nucleotide diversity (0.00438) and overall mean genetic distance (0.004 ± 0.001). The significant negative values of neutrality tests and unimodal mismatch distribution supported the demographic expansion theory in Indian L. orbonalis. Analysis of the molecular variance revealed that 93.13% of the genetic variation was within populations, and the variation among populations was only 6.87%. The pairwise genetic differentiation was also found to be low to moderate between most of the populations. Multiple haplotypes were recorded from all the populations, and both neighbour-joining tree as well as the haplotype network showed that clustering of the haplotypes was independent of the geographical location. Interpretation: Thus, it can be inferred that Indian populations of L. orbonalis have very low genetic variation levels concerning the COI gene. There is a possible occurrence of stable inherited gene flow among populations, thereby reducing genetic variation in India.

The Metaxin Mitochondrial Import Proteins: Multiple Metaxin-like Proteins in Fungi

Multiple metaxin-like proteins are shown to exist in fungi, as also found for the metaxin proteins of vertebrates and invertebrates. In vertebrates, metaxins 1 and 2 are mitochondrial membrane proteins that function in the import of proteins into mitochondria. Fungal metaxin-like proteins were identified by criteria including their homology with human metaxins and the presence of characteristic GST_N_Metaxin, GST_C_Metaxin, and Tom37 protein domains. Fungi in different taxonomic divisions (phyla) were found to possess multiple metaxin-like proteins. These include the Ascomycota, Basidiomycota, Blastocladiomycota, Chytridiomycota, Mucoromycota, Neocallimastigomycota, and Zoopagomycota divisions. Most fungi with multiple metaxin-like proteins contain two proteins, designated MTXa and MTXb. Amino acid sequence alignments show a high degree of homology among MTXa proteins, with over 60% amino acid identities, and also among MTXb proteins of fungi in the same division. But very little homology is observed in aligning MTXa with MTXb proteins of the same or different fungi. Both the MTXa proteins and MTXb proteins have the protein domains that characterize the metaxins and metaxin-like proteins: GST_N_Metaxin, GST_C_Metaxin, and Tom37. The metaxins and metaxin-like proteins of vertebrates, invertebrates, plants, protists, and bacteria all possess these domains. The secondary structures of MTXa and MTXb proteins are both dominated by similar patterns of α-helical segments, but extensive β-strand segments are absent. Nine highly conserved α-helical segments are present, the same as other metaxins and metaxin-like proteins. Phylogenetic analysis reveals that MTXa and MTXb proteins of fungi form two separate and distinct groups. These groups are also separate from the groups of vertebrate metaxins, metaxin-related Sam37 proteins of yeasts, and metaxin-like FAXC proteins.

A Novel Real Time PCR Method for the Detection and Quantification of Didymella pinodella in Symptomatic and Asymptomatic Plant Hosts

Didymella pinodella is the major pathogen of the pea root rot complex in Europe. This wide host range pathogen often asymptomatically colonizes its hosts, making the control strategies challenging. We developed a real-time PCR assay for the detection and quantification of D. pinodella based on the TEF-1 alpha gene sequence alignments. The assay was tested for specificity on a 54-isolate panel representing 35 fungal species and further validated in symptomatic and asymptomatic pea and wheat roots from greenhouse tests. The assay was highly consistent across separate qPCR reactions and had a quantification/detection limit of 3.1 pg of target DNA per reaction in plant tissue. Cross-reactions were observed with DNA extracts of five Didymella species. The risk of cross contamination, however, is low as the non-targets have not been associated with pea previously and they were amplified with at least 1000-fold lower sensitivity. Greenhouse inoculation tests revealed a high correlation between the pathogen DNA quantities in pea roots and pea root rot severity and biomass reduction. The assay also detected D. pinodella in asymptomatic wheat roots, which, despite the absence of visible root rot symptoms, caused wheat biomass reduction. This study provides new insights into the complex life style of D. pinodella and can assist in better understanding the pathogen survival and spread in the environment.

Embeddings from protein language models predict conservation and variant effects

The emergence of SARS-CoV-2 variants stressed the demand for tools allowing to interpret the effect of single amino acid variants (SAVs) on protein function. While Deep Mutational Scanning (DMS) sets continue to expand our understanding of the mutational landscape of single proteins, the results continue to challenge analyses. Protein Language Models (pLMs) use the latest deep learning (DL) algorithms to leverage growing databases of protein sequences. These methods learn to predict missing or masked amino acids from the context of entire sequence regions. Here, we used pLM representations (embeddings) to predict sequence conservation and SAV effects without multiple sequence alignments (MSAs). Embeddings alone predicted residue conservation almost as accurately from single sequences as ConSeq using MSAs (two-state Matthews Correlation Coefficient—MCC—for ProtT5 embeddings of 0.596 ± 0.006 vs. 0.608 ± 0.006 for ConSeq). Inputting the conservation prediction along with BLOSUM62 substitution scores and pLM mask reconstruction probabilities into a simplistic logistic regression (LR) ensemble for Variant Effect Score Prediction without Alignments (VESPA) predicted SAV effect magnitude without any optimization on DMS data. Comparing predictions for a standard set of 39 DMS experiments to other methods (incl. ESM-1v, DeepSequence, and GEMME) revealed our approach as competitive with the state-of-the-art (SOTA) methods using MSA input. No method outperformed all others, neither consistently nor statistically significantly, independently of the performance measure applied (Spearman and Pearson correlation). Finally, we investigated binary effect predictions on DMS experiments for four human proteins. Overall, embedding-based methods have become competitive with methods relying on MSAs for SAV effect prediction at a fraction of the costs in computing/energy. Our method predicted SAV effects for the entire human proteome (~ 20 k proteins) within 40 min on one Nvidia Quadro RTX 8000. All methods and data sets are freely available for local and online execution through bioembeddings.com, https://github.com/Rostlab/VESPA, and PredictProtein.

Genetic Diversity and Molecular Epidemiology of Circulating Respiratory Syncytial Virus in Central Taiwan, 2008–2017

In this study, we investigated the molecular evolution and phylodynamics of respiratory syncytial virus (RSV) over 10 consecutive seasons (2008–2017) and the genetic variability of the RSV genotypes ON1 and BA in central Taiwan. The ectodomain region of the G gene was sequenced for genotyping. The nucleotide and deduced amino acid sequences of the second hypervariable region of the G protein in RSV ON1 and BA were analyzed. A total of 132 RSV-A and 81 RSV-B isolates were obtained. Phylogenetic analysis revealed that the NA1, ON1, and BA9 genotypes were responsible for the RSV epidemics in central Taiwan in the study period. For RSV-A, the NA1 genotype predominated during the 2008–2011 seasons. The ON1 genotype was first detected in 2011 and replaced NA1 after 2012. For RSV-B, the BA9 and BA10 genotypes cocirculated from 2008 to 2010, but the BA9 genotype has predominated since 2012. Amino acid sequence alignments revealed the continuous evolution of the G gene in the ectodomain region. The predicted N-glycosylation sites were relatively conserved in the ON1 (site 237 and 318) and BA9 (site 296 and 310) genotype strains. Our results contribute to the understanding and prediction of the temporal evolution of RSV at the local level.

fastMSA: Accelerating Multiple Sequence Alignment with Dense Retrieval on Protein Language

Evolutionarily related sequences provide information for the protein structure and function. Multiple sequence alignment, which includes homolog searching from large databases and sequence alignment, is efficient to dig out the information and assist protein structure and function prediction, whose efficiency has been proved by AlphaFold. Despite the existing tools for multiple sequence alignment, searching homologs from the entire UniProt is still time-consuming. Considering the success of AlphaFold, foreseeably, large- scale multiple sequence alignments against massive databases will be a trend in the field. It is very desirable to accelerate this step. Here, we propose a novel method, fastMSA, to improve the speed significantly. Our idea is orthogonal to all the previous accelerating methods. Taking advantage of the protein language model based on BERT, we propose a novel dual encoder architecture that can embed the protein sequences into a low-dimension space and filter the unrelated sequences efficiently before running BLAST. Extensive experimental results suggest that we can recall most of the homologs with a 34-fold speed-up. Moreover, our method is compatible with the downstream tasks, such as structure prediction using AlphaFold. Using multiple sequence alignments generated from our method, we have little performance compromise on the protein structure prediction with much less running time. fastMSA will effectively assist protein sequence, structure, and function analysis based on homologs and multiple sequence alignment.

High-Resolution, Multidimensional Phylogenetic Metrics Identify Class I Aminoacyl-tRNA Synthetase Evolutionary Mosaicity and Inter-modular Coupling

The provenance of the aminoacyl-tRNA synthetases (aaRS) poses challenging questions because of their role in the emergence and evolution of genetic coding. We investigate evidence about their ancestry from curated structure-based multiple sequence alignments of a structurally invariant “scaffold” shared by all 10 canonical Class I aaRS. Three uncorrelated phylogenetic metrics—residue-by-residue conservation, its variance, and row-by-row cladistic congruence—imply that the Class I scaffold is a mosaic assembled from distinct, successive genetic sources. These data are especially significant in light of: (i) experimental fragmentations of the Class I scaffold into three partitions that retain catalytic activities in proportion to their length; and (ii) evidence that two of these partitions arose from an ancestral Class I aaRS gene encoding a Class II ancestor in frame on the opposite strand. Phylogenetic metrics of different modules vary in accordance with their presumed functionality. A 46-residue Class I “protozyme” roots the Class I molecular tree prior to the adaptive radiation of the Rossmann dinucleotide binding fold that refined substrate discrimination. Such rooting is consistent with near simultaneous emergence of genetic coding and the origin of the proteome, resolving a conundrum posed by previous inferences that Class I aaRS evolved long after the genetic code had been implemented in an RNA world. Further, pinpointing discontinuous enhancements of aaRS fidelity establishes a timeline for the growth of coding from a binary amino acid alphabet.

Plastics degradation by hydrolytic enzymes: the Plastics-Active Enzymes Database - PAZy

Petroleum based plastics are durable and accumulate in all ecological niches. Knowledge on enzymatic degradation is sparse. Today, less than 50 verified plastics-active enzymes are known. First examples of enzymes acting on the polymers polyethylene terephthalate (PET) and polyurethane (PUR) have been reported together with a detailed biochemical and structural description. Further, very few polyamide (PA) oligomer active enzymes are known. In this paper, the current known enzymes acting on the synthetic polymers PET and PUR are briefly summarized, their published activity data were collected and integrated into a comprehensive open access database. The Plastics-Active Enzymes Database (PAZy) represents an inventory of known and experimentally verified plastics-active enzymes. Almost 3000 homologues of PET-active enzymes were identified by profile hidden Markov models. Over 2000 homologues of PUR-active enzymes were identified by BLAST. Based on multiple sequence alignments, conservation analysis identified the most conserved amino acids, and sequence motifs for PET- and PUR-active enzymes were derived.