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.Peer Reviewe

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

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.Peer Reviewe

Development of a proteomic application for the analysis of multidrug-resistant bacterial isolates in microbiological diagnostics

Multiresistente Erreger stellen laut WHO (World Health Organization) eine der 10 größten gesundheitlichen Bedrohungen der Menschheit dar [5-7]. Die effiziente Bekämpfung dieser Erreger ist von höchster Wichtigkeit für den Erhalt der modernen Medizin [8]. Dies kann durch eine genaue Erregeridentifizierung in Kombination mit rationaler Nutzung von Antibiotika erreicht werden. Um eine effiziente antimikrobielle Behandlung zu gewährleisten, ist neben der Resistenzbestimmung auch die Speziesbestimmung erforderlich. Momentan gibt es keine Methode in der klinisch-mikrobiologischen Diagnostik, die beides vereint. In der letzten Dekade kam es in der molekularen klinischen Diagnostik zu einigen revolutionären Entwicklungen. Darunter die Etablierung der „Matrix-assisted laser desorption ionisation time-of-flight-Massenspektrometrie“, kurz MALDI-TOF MS, welche eine schnelle, genaue und kostengünstige Speziesbestimmung in Kombination mit hohem Probendurchsatz ermöglicht [9, 10]. Diese wird mit molekularen Methoden wie der Polymerase-Kettenreaktion (PCR) erweitert, z.B. um antimikrobielle Resistenzen (AMR) zu detektieren. In der Regel werden jedoch weiterhin phänotypische Tests, wie die Antibiotika-Empfindlichkeitsprüfung (AST) zur Resistenzbestimmung durchgeführt, welche zeitaufwendig sind. Molekulare Detektionen sind schon länger Kandidaten in der klinischen-mikrobiologischen Diagnostik, vor allem um Protokolle zu ersetzen welche zusätzliche Schritte wie eine Anreicherung durch Anzucht oder sekundäre Inkubationen mit Antibiotika benötigen. Proteomik mittels Tandem- Massenspektrometrie gekoppelt an eine Flüssigchromatographie (LC-MS/MS) ist eine solche Technologie. Es wurde bereits gezeigt, dass die Detektion von Resistenzen durch die Analyse des Proteoms mittels LC-MS/MS möglich ist [11-15]. Der in dieser Arbeit entwickelte LC-MS/MS Workflow (rawDIAtect) ist in der Lage, die beiden wichtigsten Fragen der klinischen Mikrobiologie, nämlich Spezies- und Resistenzbestimmung, mittels Nutzung einer Methode zu beantworten und hat zudem das Potential auch weitere Fragestellungen, wie die Quantifizierung von Virulenzfaktoren, etwa von Toxinen, zu beantworten [16]. Der Workflow kann in weniger als einer 1 Stunde einen vollständigen Bericht über die Spezies sowie das Resistenzspektrum eines Isolates liefern. Die Kombination von LC-MS1-Daten zur Speziesbestimmung und der Einsatz von DIA-Auswertemethoden zur Resistenzbestimmung ist momentan einzigartig für die klinische MS-basierte Diagnostik. Anders als bei bisherigen Protokollen werden bei rawDIAtect nicht nur einzelne Antibiotikaresistenzen detektiert, sondern das gesamte Proteom aufgenommen. Der 1h- rawDIAtect-Workflow weist für ein Panel von 147 Bakterienisolaten bestehend aus 10 Gram- negativen sowie 2 Gram-positiven bakteriellen Spezies mit 30 AMR-Determinanten eine Sensitivität von 93 % und eine Spezifität von 99,3 % auf. Damit ist rawDIAtect ein vielsprechender Kandidat, die bakterielle Diagnostik Einzug zu finden.According to the WHO (World Health Organization), multidrug-resistant pathogens are one of the 10 greatest threats to humanity [5-7]. The concrete and efficient control of these pathogens is of paramount importance for the preservation of modern medicine [8]. This can be achieved through accurate pathogen identification combined with rational use of antibiotics. To ensure efficient antimicrobial treatment, species identification is required in addition to resistance determination. Currently, there is no method in routine diagnostics that combines both. The last decade has seen some revolutionary developments in molecular clinical diagnostics. These include the establishment of "matrix-assisted laser desorption ionization time-of-flight mass spectrometry", or MALDI-TOF MS for short, which enables rapid, accurate and cost- effective species determination in combination with high sample throughput [9, 10]. This is extended with molecular methods such as polymerase chain reaction (PCR) to detect antimicrobial resistance (AMR). However, phenotypic tests such as antibiotic susceptibility testing (AST) are usually carried out further to determine resistance, which are time- consuming. Molecular detection has long been a candidate in clinical diagnostics, especially to replace protocols that require additional steps such as enrichment by culturing or secondary incubations with antibiotics. Proteomics using tandem mass spectrometry coupled to liquid chromatography (LC-MS/MS) is one such technology. It has already been shown that the detection of resistance is possible by analysing the proteome using LC-MS/MS [11-15]. The LC-MS/MS workflow (rawDIAtect) developed in this work is able to answer the two most important questions in clinical microbiology, namely species and resistance determination, using one method and also has the potential to answer further questions, such as the quantification of virulence factors, for example of toxins [16]. The workflow can provide a complete report on the species as well as the resistance spectrum of an isolate in under 1 h. The combination of LC-MS1 data for species identification and the use of state-of-the-art DIA evaluation methods for resistance determination is currently unique for clinical MS-based diagnostics. Unlike previous protocols, rawDIAtect not only detects individual antibiotic resistances, but also the entire proteome. The 1h-rawDIAtect workflow has a sensitivity of 93 % and a specificity of 99.3 % for 30 AMR determinants for a panel of 147 bacterial isolates across 10 Gram-negative and 2 Gram-positive bacterial species. This makes rawDIAtect a promising candidate to enter the field of bacterial diagnostics

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

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

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.Peer Reviewe

Novel Plant-Associated <i>Brevibacillus</i> and <i>Lysinibacillus</i> 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

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.Bundesministerium für Bildung und Forschung (BMBF)National Foundation for Science and Technology Development (NAFOSTED)Ministry of Science and Technology (MOST) in VietnamPeer Reviewe