Plant-Associated Representatives of the Bacillus cereus Group Are a Rich Source of Antimicrobial Compounds.

Seventeen bacterial strains able to suppress plant pathogens have been isolated from healthy Vietnamese crop plants and taxonomically assigned as members of the Bacillus cereus group. In order to prove their potential as biocontrol agents, we perform a comprehensive analysis that included the whole-genome sequencing of selected strains and the mining for genes and gene clusters involved in the synthesis of endo- and exotoxins and secondary metabolites, such as antimicrobial peptides (AMPs). Kurstakin, thumolycin, and other AMPs were detected and characterized by different mass spectrometric methods, such as MALDI-TOF-MS and LIFT-MALDI-TOF/TOF fragment analysis. Based on their whole-genome sequences, the plant-associated isolates were assigned to the following species and subspecies: B. cereus subsp. cereus (6), B. cereus subsp. bombysepticus (5), Bacillus tropicus (2), and Bacillus pacificus. These three isolates represent novel genomospecies. Genes encoding entomopathogenic crystal and vegetative proteins were detected in B. cereus subsp. bombysepticus TK1. The in vitro assays revealed that many plant-associated isolates enhanced plant growth and suppressed plant pathogens. Our findings indicate that the plant-associated representatives of the B. cereus group are a rich source of putative antimicrobial compounds with potential in sustainable agriculture. However, the presence of virulence genes might restrict their application as biologicals in agriculture.

Two plant-associated Bacillus velezensis strains selected after genome analysis, metabolite profiling, and with proved biocontrol potential, were enhancing harvest yield of coffee and black pepper in large field trials.

Elimination of chemically synthesized pesticides, such as fungicides and nematicides, in agricultural products is a key to successful practice of the Vietnamese agriculture. We describe here the route for developing successful biostimulants based on members of the Bacillus subtilis species complex. A number of endospore-forming Gram-positive bacterial strains with antagonistic action against plant pathogens were isolated from Vietnamese crop plants. Based on their draft genome sequence, thirty of them were assigned to the Bacillus subtilis species complex. Most of them were assigned to the species Bacillus velezensis. Whole genome sequencing of strains BT2.4 and BP1.2A corroborated their close relatedness to B. velezensis FZB42, the model strain for Gram-positive plant growth-promoting bacteria. Genome mining revealed that at least 15 natural product biosynthesis gene clusters (BGCs) are well conserved in all B. velezensis strains. In total, 36 different BGCs were identified in the genomes of the strains representing B. velezensis, B. subtilis, Bacillus tequilensis, and Bacillus. altitudinis. In vitro and in vivo assays demonstrated the potential of the B. velezensis strains to enhance plant growth and to suppress phytopathogenic fungi and nematodes. Due to their promising potential to stimulate plant growth and to support plant health, the B. velezensis strains TL7 and S1 were selected as starting material for the development of novel biostimulants, and biocontrol agents efficient in protecting the important Vietnamese crop plants black pepper and coffee against phytopathogens. The results of the large-scale field trials performed in the Central Highlands in Vietnam corroborated that TL7 and S1 are efficient in stimulating plant growth and protecting plant health in large-scale applications. It was shown that treatment with both bioformulations resulted in prevention of the pathogenic pressure exerted by nematodes, fungi, and oomycetes, and increased harvest yield in coffee, and pepper.

Increasing Proteome Depth While Maintaining Quantitative Precision in Short-Gradient Data-Independent Acquisition Proteomics.

The combination of short liquid chromatography (LC) gradients and data-independent acquisition (DIA) by mass spectrometry (MS) has proven its huge potential for high-throughput proteomics. However, the optimization of isolation window schemes resulting in a certain number of data points per peak (DPPP) is understudied, although it is one of the most important parameters for the outcome of this methodology. In this study, we show that substantially reducing the number of DPPP for short-gradient DIA massively increases protein identifications while maintaining quantitative precision. This is due to a large increase in the number of precursors identified, which keeps the number of data points per protein almost constant even at long cycle times. When proteins are inferred from its precursors, quantitative precision is maintained at low DPPP while greatly increasing proteomic depth. This strategy enabled us to quantify 6018 HeLa proteins (>80 000 precursor identifications) with coefficients of variation below 20% in 30 min using a Q Exactive HF, which corresponds to a throughput of 29 samples per day. This indicates that the potential of high-throughput DIA-MS has not been fully exploited yet. Data are available via ProteomeXchange with identifier PXD036451.

Novel Plant-Associated Brevibacillus and Lysinibacillus Genomospecies Harbor a Rich Biosynthetic Potential of Antimicrobial Compounds.

We have previously reported the draft genome sequences of 59 endospore-forming Gram-positive bacterial strains isolated from Vietnamese crop plants due to their ability to suppress plant pathogens. Based on their draft genome sequence, eleven of them were assigned to the Brevibacillus and one to the Lysinibacillus genus. Further analysis including full genome sequencing revealed that several of these strains represent novel genomospecies. In vitro and in vivo assays demonstrated their ability to promote plant growth, as well as the strong biocontrol potential of Brevibacilli directed against phytopathogenic bacteria, fungi, and nematodes. Genome mining identified 157 natural product biosynthesis gene clusters (BGCs), including 36 novel BGCs not present in the MIBiG data bank. Our findings indicate that plant-associated Brevibacilli are a rich source of putative antimicrobial compounds and might serve as a valuable starting point for the development of novel biocontrol agents.

Genome sequence data of Bacillus velezensis BP1.2A and BT2.4.

Here, we report the complete genome sequence data of the biocontrol strains Bacillus velezensis BP1.2A and BT2.4 isolated from Vietnamese crop plants. The size of the genomes is 3,916,868 bp (BP1.2A), and 3,922,686 bp (BT2.4), respectively. The BioProjects have been deposited at NCBI GenBank. The GenBank accession numbers for the B. velezensis strains are PRJNA634914 (BP1.2A) and PRJNA634832 (BT2.4) for the BioProjects, CP085504 (BP1.2A) and CP085505 (BT2.4) for the chromosomes, GCA_013284785.2 (BP2.1A), and GCA_013284785.2 (BT2.4) for GenBank assembly accessions, and SAMN15012571 (BP1.2A) and SAMN15009897 (BT2.4) for the BioSamples. Both genomes were closely related to FZB42, the model strain for plant growth promoting bacilli.

Context-aware genomic surveillance reveals hidden transmission of a carbapenemase-producing Klebsiella pneumoniae.

Genomic surveillance can inform effective public health responses to pathogen outbreaks. However, integration of non-local data is rarely done. We investigate two large hospital outbreaks of a carbapenemase-carrying Klebsiella pneumoniae strain in Germany and show the value of contextual data. By screening about 10 000 genomes, over 400 000 metagenomes and two culture collections using in silico and in vitro methods, we identify a total of 415 closely related genomes reported in 28 studies. We identify the relationship between the two outbreaks through time-dated phylogeny, including their respective origin. One of the outbreaks presents extensive hidden transmission, with descendant isolates only identified in other studies. We then leverage the genome collection from this meta-analysis to identify genes under positive selection. We thereby identify an inner membrane transporter (ynjC) with a putative role in colistin resistance. Contextual data from other sources can thus enhance local genomic surveillance at multiple levels and should be integrated by default when available.

Unbiased Antimicrobial Resistance Detection from Clinical Bacterial Isolates Using Proteomics.

Antimicrobial resistance (AMR) poses an increasing challenge for therapy and clinical management of bacterial infections. Currently, antimicrobial resistance detection relies on phenotypic assays, which are performed independently from species identification. Sequencing-based approaches are possible alternatives for AMR detection, although the analysis of proteins should be superior to gene or transcript sequencing for phenotype prediction as the actual resistance to antibiotics is almost exclusively mediated by proteins. In this proof-of-concept study, we present an unbiased proteomics workflow for detecting both bacterial species and AMR-related proteins in the absence of secondary antibiotic cultivation within <4 h from a primary culture. The workflow was designed to meet the needs in clinical microbiology. It introduces a new data analysis concept for bacterial proteomics, and a software (rawDIAtect) for the prediction and reporting of AMR from peptide identifications. The method was validated using a sample cohort of 7 bacterial species and 11 AMR determinants represented by 13 protein isoforms, which resulted in a sensitivity of 98% and a specificity of 100%.

Draft Genome Sequences of 59 Endospore-Forming Gram-Positive Bacteria Associated with Crop Plants Grown in Vietnam.

We report the draft genome sequences of 59 Gram-positive bacterial strains that were isolated from Vietnamese crop plants. The strains were assigned to nine different Bacillus and Brevibacillus species. Ten strains classified as being a Bacillus sp. (3 strains), Brevibacillus sp. (6 strains), or Lysinibacillus sp. (1 strain) could not be identified to the species level.

Identification of Microorganisms by Liquid Chromatography-Mass Spectrometry (LC-MS1) and in Silico Peptide Mass Libraries.

Over the past decade, modern methods of MS (MS) have emerged that allow reliable, fast and cost-effective identification of pathogenic microorganisms. Although MALDI-TOF MS has already revolutionized the way microorganisms are identified, recent years have witnessed also substantial progress in the development of liquid chromatography (LC)-MS based proteomics for microbiological applications. For example, LC-tandem MS (LC-MS2) has been proposed for microbial characterization by means of multiple discriminative peptides that enable identification at the species, or sometimes at the strain level. However, such investigations can be laborious and time-consuming, especially if the experimental LC-MS2 data are tested against sequence databases covering a broad panel of different microbiological taxa. In this proof of concept study, we present an alternative bottom-up proteomics method for microbial identification. The proposed approach involves efficient extraction of proteins from cultivated microbial cells, digestion by trypsin and LC-MS measurements. Peptide masses are then extracted from MS1 data and systematically tested against an in silico library of all possible peptide mass data compiled in-house. The library has been computed from the UniProt Knowledgebase covering Swiss-Prot and TrEMBL databases and comprises more than 12,000 strain-specific in silico profiles, each containing tens of thousands of peptide mass entries. Identification analysis involves computation of score values derived from correlation coefficients between experimental and strain-specific in silico peptide mass profiles and compilation of score ranking lists. The taxonomic positions of the microbial samples are then determined by using the best-matching database entries. The suggested method is computationally efficient - less than 2 mins per sample - and has been successfully tested by a test set of 39 LC-MS1 peak lists obtained from 19 different microbial pathogens. The proposed method is rapid, simple and automatable and we foresee wide application potential for future microbiological applications.

Isolation Window Optimization of Data-Independent Acquisition Using Predicted Libraries for Deep and Accurate Proteome Profiling.

In silico spectral library prediction of all possible peptides from whole organisms has a great potential for improving proteome profiling by data-independent acquisition (DIA) and extending its scope of application. In combination with other recent improvements in the field of mass spectrometry (MS)-based proteomics, including sample preparation, peptide separation, and data analysis, we aimed to uncover the full potential of such an advanced DIA strategy by optimization of the data acquisition. The results demonstrate that the combination of high-quality in silico libraries, reproducible and high-resolution peptide separation using micropillar array columns, as well as neural network supported data analysis enables the use of long MS scan cycles without impairing the quantification performance. The study demonstrates that mean coefficient of variations of 4% were obtained even at only 1.5 data points per peak (full width at half-maximum) across different gradient lengths, which in turn improved proteome coverage up to more than 8000 proteins from HeLa cells using empirically corrected libraries and more than 7000 proteins using a whole human in silico predicted library. These data were obtained using a Q Exactive orbitrap mass spectrometer with moderate scanning speed (12 Hz) and perform very well in comparison to recent studies using more advanced MS instruments, which underline the high potential of this optimization strategy for various applications in clinical proteomics, microbiology, and molecular biology.

The N-terminal domains of the paralogous HycE and NuoCD govern assembly of the respective formate hydrogenlyase and NADH dehydrogenase complexes.

Formate hydrogenlyase (FHL) is the main hydrogen-producing enzyme complex in enterobacteria. It converts formate to CO2 and H2 via a formate dehydrogenase and a [NiFe]-hydrogenase. FHL and complex I are evolutionarily related and share a common core architecture. However, complex I catalyses the fundamentally different electron transfer from NADH to quinone and pumps protons. The catalytic FHL subunit, HycE, resembles NuoCD of Escherichia coli complex I; a fusion of NuoC and NuoD present in other organisms. The C-terminal domain of HycE harbours the [NiFe]-active site and is similar to other hydrogenases, while this domain in NuoCD is involved in quinone binding. The N-terminal domains of these proteins do not bind cofactors and are not involved in electron transfer. As these N-terminal domains are separate proteins in some organisms, we removed them in E. coli and observed that both FHL and complex I activities were essentially absent. This was due to either a disturbed assembly or to complex instability. Replacing the N-terminal domain of HycE with a 180 amino acid E. coli NuoC protein fusion did not restore activity, indicating that the domains have complex-specific functions. A FHL complex in which the N- and C-terminal domains of HycE were physically separated still retained most of its FHL activity, while the separation of NuoCD abolished complex I activity completely. Only the FHL complex tolerates physical separation of the HycE domains. Together, the findings strongly suggest that the N-terminal domains of these proteins are key determinants in complex assembly.