Biology subjects

Yoshimoto, S.

Publications and source records attributed to Yoshimoto, S..

4 recordsLinked to original sources

bioRxiv2025

Identification and functional characterization of toluene degradation genes in Acinetobacter sp. Tol 5

Microbial degradation of aromatic compounds provides sustainable solutions for environmental remediation and bioconversion. Acinetobacter sp. Tol 5 is notable for its strong adhesiveness and potential as a biocatalyst for toluene degradation; however, its toluene metabolic pathway has not been fully elucidated. In this study, genomic analysis identified a cluster of genes in Tol 5 highly similar to the well-known tod operon of Pseudomonas putida, encoding enzymes responsible for toluene metabolism. Phylogenetic analyses indicated that these tod genes, unusual among Acinetobacter species, were likely acquired through horizontal gene transfer. Transcriptomic analyses revealed that todF and todC1 are co-transcribed, while the adjacent fadL2 gene, encoding a putative outer membrane transporter corresponding to P. putida todX, is independently transcribed. Functional characterization using gene-knockout mutants revealed that TodC1, the large subunit of dioxygenase, is essential for growth on toluene, whereas FadL2 is not essential. Growth experiments further showed that the todC1 knockout mutant could metabolize benzoate, but not toluene or benzene, confirming that the TOD pathway is the primary route for toluene and benzene degradation in Tol 5. The identification of the functional TOD pathway, which is unique within Acinetobacter, provides genetic and biochemical insights for the development of Tol 5 as an efficient immobilized biocatalyst for the bioremediation and bioconversion of aromatic compounds.

microbiology↗

bioRxiv2024

A new target of multiple lysine methylation in bacteria

The methylation of {varepsilon}-amino groups in protein lysine residues is known to be an important posttranslational modification in eukaryotes. This modification plays a pivotal role in the regulation of diverse biological processes, including epigenetics, transcriptional control, and cellular signaling. Although less studied in prokaryotes, recent research has begun to reveal the potential role of methylation in modulating bacterial immune evasion and adherence to host cells. In this study, we analyzed the cell surface proteins of the toluene-degrading bacterium Acinetobacter sp. Tol 5 by label-free liquid chromatography-mass spectrometry (LC-MS) and found that the lysine residues of its trimeric autotransporter adhesin (TAA), AtaA, are methylated. Over 130 lysine residues of AtaA, consisting of 3,630 amino acids and containing 232 lysine residues, were methylated. We identified the outer membrane protein lysine methyltransferase (OM PKMT) of Tol 5, KmtA, which specifically methylates the lysine residues of AtaA. In the KmtA-deficient mutant, most lysine methylations on AtaA were absent, indicating that KmtA is responsible for the methylation of multiple lysine residues throughout AtaA. Bioinformatic analysis revealed that the OM PKMT genes were widely distributed among gram-negative bacteria, including pathogens with TAAs that promote infectivity, such as Burkholderia mallei and Haemophilus influenzae. Although KmtA has sequence similarities to the OM PKMTs of Rickettsia involved in infectivity, KmtA-like PKMTs formed a distinct cluster from those of the Rickettsia type according to the clustering analysis, suggesting that they are new types of PKMTs. Furthermore, the deletion of Tol 5 KmtA led to an increase in AtaA on the cell surface and enhanced bacterial adhesion, resulting in slower growth. SignificanceMethylation of lysine residues is a posttranslational modification that plays diverse physiological roles in eukaryotes. In prokaryotes however, lysine methylation has been studied only in a limited number of pathogenic bacteria. In this study, we found novel lysine methylation across multiple residues of an outer membrane protein and its methyltransferase, KmtA, in a bacterium from activated sludge. KmtA, along with rickettsial outer membrane protein lysine methyltransferases, which are known to be involved in bacterial pathogenicity, exists in many species of gram-negative bacteria. This finding suggests that methylations are ubiquitous in prokaryotes and are involved in a variety of functions, offering potential strategies for controlling bacterial infections and enhancing the functions of beneficial bacteria for biotechnological applications.

microbiology↗

bioRxiv2023

Structural and functional insights into the complex formation of a trimeric autotransporter adhesin with a peptidoglycan-binding periplasmic protein

Trimeric autotransporter adhesins (TAAs) are outer membrane (OM) proteins that are widely distributed in gram-negative bacteria and are involved primarily in adhesion to biotic and abiotic surfaces, cell agglutination, and biofilm formation. TAAs consist of a passenger domain, which is secreted onto the cell surface, and a transmembrane domain, which forms a pore in the OM to secrete and anchor the passenger domain. Because the interactions between TAAs and chaperones or dedicated auxiliary proteins during secretion are short-lived, TAAs are thought to reside on the OM without forming complexes with other proteins after secretion. In this study, we aimed to clarify the interactions between an Acinetobacter TAA, AtaA, and a peptidoglycan (PG)-binding periplasmic protein, TpgA. Pull-down assays using recombinant proteins identified the interacting domains. X-ray crystallography at 2.6 [A] resolution revealed an A3B3 heterohexameric complex structure composed of the N-terminal domain of TpgA and the transmembrane domain of AtaA. TpgA-N consists of two short helices and three antiparallel {beta} strands, yielding an {beta}{beta}{beta} topology similar to BamE. However, the regions corresponding to BamE interfaces with BamA and BamD differ in TpgA-N. All-atom molecular dynamics simulations and mutational assays revealed that both electrostatic and hydrophobic interactions contribute to stable complex formation. Bioinformatic analyses indicate that the TAA-TpgA complex occurs in a wide range of species. These findings will contribute to a better understanding of TAAs and the cell envelope. ImportanceGram-negative bacteria have specialized secretion systems (SSs) that translocate molecules from the cytoplasm to the extracellular space. Type V SSs have a simpler structure consisting of a functional passenger domain and a transmembrane domain involved in the secretion and anchoring of the passenger domain. Here, we provide the first direct evidence that a trimeric autotransporter adhesin (TAA) exported by a type Vc system forms a stable complex with a peptidoglycan-binding periplasmic protein. The 2.6 [A] structure of the A3B3 heterohexamer, together with simulation and mutational data, reveals complementary electrostatic and hydrophobic contacts that stabilize flexible loops on the periplasmic face of the TAA transmembrane barrel. Conservation of the taa-tpgA gene cassette and of key interface residues across diverse genera suggests that this coupling is a common strategy for tuning TAA stability and indicates that the envelope architecture of many TAAs, including those related to pathogenicity, is more elaborate than previously appreciated.

microbiology↗

bioRxiv2023

Development of a fast feature extraction method for SARS-CoV-2 spike sequences using amino acid physicochemical properties

COVID-19 continues to spread today, leading to an accumulation of SARS-CoV-2 virus mutations in databases, and large amounts of genomic datasets are currently available. However, due to these large datasets, utilizing this amount of sequence data without random sampling is challenging. Major difficulties for downstream analyses include the increase in the dimension size along with the conversion of sequences into numerical values when using conventional amino acid representation methods, such as one-hot encoding and k-mer-based approaches that directly reflect sequences. Moreover, these sequences are deficient in physicochemical characteristics, such as structural information and hydrophilicity; hence, they fail to accurately represent the inherent function of the given sequences. In this study, we utilized the physicochemical properties of amino acids to develop a rapid and efficient approach for extracting feature parameters that are suitable for downstream processes of machine learning, such as clustering. A fixed-length feature vector representation of a spike sequence with reduced dimensionality was obtained by converting amino acid residues into physicochemical parameters. Next, t-distributed stochastic neighbor embedding (t- SNE), a method for dimensionality reduction and visualization of high-dimensional data, was performed, followed by density-based spatial clustering of applications with noise (DBSCAN). The results show that by using the physicochemical properties of amino acids rather than conventional methods that directly represent sequences into numerical values, SARS-CoV-2 spike sequences can be clustered with sufficient accuracy and a shorter runtime. Interestingly, the clusters obtained by using amino acid properties include subclusters that are distinct from those produced utilizing the method for the direct representation of amino acid sequences. A more detailed analysis indicated that the contributing parameters of this novel cluster identified exclusively when utilizing the physicochemical properties of amino acids significantly differ from one another. This suggests that representing amino acid sequences by physicochemical properties might enable the identification of clusters with enhanced sensitivity compared to conventional methods. Author summaryOne of the major causes of the global threat of SARS-CoV-2 is the rapid emergence of its variants. While analyzing these variants is crucial for understanding the mechanism of outbreaks, the expansion of database size is becoming a barrier for effective analysis. In this study, we provide an approach that allows researchers without vast computational resources to comprehensively analyze the variants of SARS-CoV-2 spike by representing the sequences using the physicochemical properties of amino acids. The result of clusters derived using this method demonstrates not only an accuracy comparable to the conventional approaches of directly converting sequences into numerical values but also indicates the potential for more detailed clustering outcomes. The results suggest that our approach is valuable for the rapid identification of characteristic residues in new variants of SARS-CoV-2 and other viruses that may arise in the future.

bioinformatics↗