Alleles of the vacuolating cytotoxin gene (vacA) ofHelicobacter pylori vary between strains, particularly in the region encoding the signal sequence (which may be type s1 or s2) and the midregion (which may be type m1 or m2). Using a PCR-based typing system developed in the United States, we showed that 36 strains from Asia and South America were all vacA signal sequence type s1; 3 were midregion type m1 and 11 were m2, but 22 could not be typed for the vacA midregion. All strains possessedcagA (cytotoxin-associated gene A), another virulence marker. vacA nucleotide sequence analysis showed that midregion typing failure was due to base substitutions at the primer annealing sites. Using the new sequence data, we developed two new PCR-based vacA midregion typing systems, both of which correctly typed 41 U.S. strains previously typed by the old system and successfully typed all 36 of the non-U.S. strains. All previously untypeable strains were vacA m1, other than one m1/m2 hybrid. In summary, we describe and validate a simple PCR-based system for typing vacuolating cytotoxin (vacA) alleles of H. pylori and show that this system correctly identifies the signal and midregion types of vacA in 77 strains from Asia and North and South America.

The natural restoration of soils polluted by aromatic hydrocarbons such as benzene, toluene, ethylbenzene and m- and p-xylene (BTEX) may be accelerated by inoculation of specific biodegraders (bioaugmentation). Bioaugmentation mainly involves introducing bacteria that deploy their metabolic properties and adaptation potential to survive and propagate in the contaminated environment by degrading the pollutant. In order to better understand the adaptive response of cells during a transition to contaminated material, we analyzed here the genome and short-term (1 h) changes in genome-wide gene expression of the BTEX-degrading bacterium Pseudomonas veronii 1YdBTEX2 in non-sterile soil and liquid medium, both in presence or absence of toluene. We obtained a gapless genome sequence of P. veronii 1YdBTEX2 covering three individual replicons with a total size of 8 Mb, two of which are largely unrelated to current known bacterial replicons. One-hour exposure to toluene, both in soil and liquid, triggered massive transcription (up to 208-fold induction) of multiple gene clusters, such as toluene degradation pathway(s), chemotaxis and toluene efflux pumps. This clearly underlines their key role in the adaptive response to toluene. In comparison to liquid medium, cells in soil drastically changed expression of genes involved in membrane functioning (e.g., lipid composition, lipid metabolism, cell fatty acid synthesis), osmotic stress response (e.g., polyamine or trehalose synthesis, uptake of potassium) and putrescine metabolism, highlighting the immediate response mechanisms of P. veronii 1YdBTEX2 for successful establishment in polluted soil.

Understanding the adaptive responses of individual bacterial strains is crucial for microbiome engineering approaches that introduce new functionalities into complex microbiomes, such as xenobiotic compound metabolism for soil bioremediation. Adaptation requires metabolic reprogramming of the cell, which can be captured by multi-omics, but this data remains formidably challenging to interpret and predict. Here we present a new approach that combines genome-scale metabolic modeling with transcriptomics and exometabolomics, both of which are common tools for studying dynamic population behavior. As a realistic demonstration, we developed a genome-scale model of Pseudomonas veronii 1YdBTEX2, a candidate bioaugmentation agent for accelerated metabolism of mono-aromatic compounds in soil microbiomes, while simultaneously collecting experimental data of P. veronii metabolism during growth phase transitions. Predictions of the P. veronii growth rates and specific metabolic processes from the integrated model closely matched experimental observations. We conclude that integrative and network-based analysis can help build predictive models that accurately capture bacterial adaptation responses. Further development and testing of such models may considerably improve the successful establishment of bacterial inoculants in more complex systems.npj Systems Biology and Applications (2020) 6:1 ; https://doi.

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Background Bioaugmentation aims to use the capacities of specific bacterial strains inoculated into sites to enhance pollutant biodegradation. Bioaugmentation results have been mixed, which has been attributed to poor inoculant growth and survival in the field, and, consequently, moderate catalytic performance. However, our understanding of biodegradation activity mostly comes from experiments conducted under laboratory conditions, and the processes occurring during adaptation and invasion of inoculants into complex environmental microbiomes remain poorly known. The main aim of this work was thus to study the specific and different cellular reactions of an inoculant for bioaugmentation during adaptation, growth and survival in natural clean and contaminated non-sterile soils, in order to better understand factors limiting bioaugmentation. Results As inoculant we focused on the monoaromatic compound-degrading bacterium Pseudomonas veronii 1YdBTEX2. The strain proliferated in all but one soil types in presence and in absence of exogenously added toluene. RNAseq and differential genome-wide gene expression analysis illustrated both a range of common soil responses such as increased nutrient scavenging and recycling, expression of defense mechanisms, as well as environment-specific reactions, notably osmoprotection and metal homeostasis. The core metabolism of P. veronii remained remarkably constant during exponential growth irrespective of the environment, with slight changes in cofactor regeneration pathways, possibly needed for balancing defense reactions. Conclusions P. veronii displayed a versatile global program, enabling it to adapt to a variety of soil environments in the presence and even in absence of its target pollutant toluene. Our results thus challenge the widely perceived dogma of poor survival and growth of exogenous inoculants in complex microbial ecosystems such as soil and provide a further basis to developing successful bioaugmentation strategies.

23Understanding the adaptive responses of individual bacterial strains is crucial for microbiome 24 engineering approaches that introduce new functionalities into complex microbiomes, such as 25 xenobiotic compound metabolism for soil bioremediation. Adaptation requires metabolic 26 reprogramming of the cell, which can be captured by multi-omics, but this data remains 27 formidably challenging to interpret and predict. Here we present a new approach that combines 28 genome-scale metabolic modeling with transcriptomics and exometabolomics, both of which are 29 common tools for studying dynamic population behavior. As a realistic demonstration, we 30 developed a genome-scale model of Pseudomonas veronii 1YdBTEX2, a candidate 31 bioaugmentation agent for accelerated metabolism of mono-aromatic compounds in soil 32 microbiomes, while simultaneously collecting experimental data of P. veronii metabolism during 33 growth phase transitions. Predictions of the P. veronii growth rates and specific metabolic 34 processes from the integrated model closely matched experimental observations. We conclude 35 that integrative and network-based analysis can help build predictive models that accurately 36 capture bacterial adaptation responses. Further development and testing of such models may 37 considerably improve the successful establishment of bacterial inoculants in more complex 38 systems. 39 40 41 42 43 44 45 46 47 48 49 50 3

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