Phenotype microarrays for high-throughput phenotypic testing and assay of gene function

Addressing genome scale design tradeoffs in Pseudomonas putida for bioconversion of an aromatic carbon source

Genome-scale metabolic models (GSMM) are commonly used to identify gene deletion sets that result in growth coupling and pairing product formation with substrate utilization and can improve strain performance beyond levels typically accessible using traditional strain engineering approaches. However, sustainable feedstocks pose a challenge due to incomplete high-resolution metabolic data for non-canonical carbon sources required to curate GSMM and identify implementable designs. Here we address a four-gene deletion design in the Pseudomonas putida KT2440 strain for the lignin-derived non-sugar carbon source, p-coumarate (p-CA), that proved challenging to implement. We examine the performance of the fully implemented design for p-coumarate to glutamine, a useful biomanufacturing intermediate. In this study glutamine is then converted to indigoidine, an alternative sustainable pigment and a model heterologous product that is commonly used to colorimetrically quantify glutamine concentration. Through proteomics, promoter-variation, and growth characterization of a fully implemented gene deletion design, we provide evidence that aromatic catabolism in the completed design is rate-limited by fumarase hydratase (FUM) enzyme activity in the citrate cycle and requires careful optimization of another fumarate hydratase protein (PP_0897) expression to achieve growth and production. A double sensitivity analysis also confirmed a strict requirement for fumarate hydratase activity in the strain where all genes in the growth coupling design have been implemented. Metabolic cross-feeding experiments were used to examine the impact of complete removal of the fumarase hydratase reaction and revealed an unanticipated nutrient requirement, suggesting additional functions for this enzyme. While a complete implementation of the design was achieved, this study highlights the challenge of completely inactivating metabolic reactions encoded by under-characterized proteins, especially in the context of multi-gene edits.

Biomolecule screen identifies several inhibitors of Salmonella enterica surface colonization

Salmonella enterica is a foodborne pathogen commonly found in agricultural facilities; its prevalence, as well as increasing levels of disinfectant- and antibiotic-resistance, has significant costs for agriculture as well as human health. In an effort to identify potential new inhibitors of S. enterica on abiotic surfaces, we developed a biomolecule screen of nutrient-type compounds because nutrients would have lower toxicity in animal facilities and bacterial nutrient utilization pathways might prove less susceptible to the development of bacterial resistance. After screening 285 nutrient-type compounds, we identified ten that significantly inhibited the ability of S. enterica to colonize a plastic surface. After conducting a dose-response curve, salicylic acid was selected for further testing due to its low minimal inhibitory concentration (62.5 μM) as well as a low total inhibitory concentration (250 μM). Salicylic acid was also able to inhibit surface colonization of a wide range of bacterial pathogens, suggesting that our biomolecule screen might have broader application beyond S. enterica. Finally, we determined that salicylic acid was also able to inhibit S. enterica colonization of an organic surface on eggshells. Together, these results suggest that nutrient-type biomolecules may provide an avenue for preventing resistant bacteria from contaminating surfaces.

Pan-genome-scale metabolic modeling of Bacillus subtilis reveals functionally distinct groups

Bacillus subtilis is an important industrial and environmental microorganism known to occupy many niches and produce many compounds of interest. Although it is one of the best-studied organisms, much of this focus including the reconstruction of genome-scale metabolic models has been placed on a few key laboratory strains. Here, we substantially expand these prior models to pan-genome-scale, representing 481 genomes of B. subtilis with 2,315 orthologous gene clusters, 1,874 metabolites, and 2,239 reactions. Furthermore, we incorporate data from carbon utilization experiments for eight strains to refine and validate its metabolic predictions. This comprehensive pan-genome model enables the assessment of strain-to-strain differences related to nutrient utilization, fermentation outputs, robustness, and other metabolic aspects. Using the model and phenotypic predictions, we divide B. subtilis strains into five groups with distinct patterns of behavior that correlate across these features. The pan-genome model offers deep insights into B. subtilis' metabolism as it varies across environments and provides an understanding as to how different strains have adapted to dynamic habitats.

IMPORTANCE

As the volume of genomic data and computational power have increased, so has the number of genome-scale metabolic models. These models encapsulate the totality of metabolic functions for a given organism. Bacillus subtilis strain 168 is one of the first bacteria for which a metabolic network was reconstructed. Since then, several updated reconstructions have been generated for this model microorganism. Here, we expand the metabolic model for a single strain into a pan-genome-scale model, which consists of individual models for 481 B. subtilis strains. By evaluating differences between these strains, we identified five distinct groups of strains, allowing for the rapid classification of any particular strain. Furthermore, this classification into five groups aids the rapid identification of suitable strains for any application.

Chromosomal integrons are genetically and functionally isolated units of genomes

Integrons are genetic elements that increase the evolvability of bacteria by capturing new genes and stockpiling them in arrays. Sedentary chromosomal integrons (SCIs) can be massive and highly stabilized structures encoding hundreds of genes, whose function remains generally unknown. SCIs have co-evolved with the host for aeons and are highly intertwined with their physiology from a mechanistic point of view. But, paradoxically, other aspects, like their variable content and location within the genome, suggest a high genetic and functional independence. In this work, we have explored the connection of SCIs to their host genome using as a model the Superintegron (SI), a 179-cassette long SCI in the genome of Vibrio cholerae N16961. We have relocated and deleted the SI using SeqDelTA, a novel method that allows to counteract the strong stabilization conferred by toxin-antitoxin systems within the array. We have characterized in depth the impact in V. cholerae's physiology, measuring fitness, chromosome replication dynamics, persistence, transcriptomics, phenomics, natural competence, virulence and resistance against protist grazing. The deletion of the SI did not produce detectable effects in any condition, proving that-despite millions of years of co-evolution-SCIs are genetically and functionally isolated units of genomes.

PhenoMetaboDiff: R Package for Analysis and Visualization of Phenotype Microarray Data

BACKGROUND

PhenoMetaboDiff is a novel R package for computational analysis and visualization of data generated by Biolog Phenotype Mammalian Microarrays (PM-Ms). These arrays measure the energy production of mammalian cells in different metabolic environments, assess the metabolic activity of cells exposed to various drugs or energy sources, and compare the metabolic profiles of cells from individuals affected by specific disorders versus healthy controls.

METHODS

PhenoMetaboDiff has several modules that facilitate statistical analysis by sample comparisons using non-parametric Mann-Whitney U-test, the integration of the OPM package (an R package for analysing OmniLog® phenotype microarray data) for robust file conversion, and calculation of slope and area under the curve (AUC). In addition, the built-in visualization allows specific wells to be visualized in selected pathways for a particular time slice.

RESULTS

Compared to the standard OPM package, the features developed in PhenoMetaboDiff assess metabolic profiles by employing statistical tests and visualize the dynamic nature of the energy production in several conditions. Examples of how this package can be used are demonstrated for several rare disease conditions. The incorporation of a graphical user interface expands the utility of this program to both expert and novice users of R.

CONCLUSIONS

PhenoMetaboDiff makes the deployment of the cutting-edge Biolog system available to any researcher.

A genome-scale metabolic model of a globally disseminated hyperinvasive M1 strain of Streptococcus pyogenes

Streptococcus pyogenes is responsible for a range of diseases in humans contributing significantly to morbidity and mortality. Among more than 200 serotypes of S. pyogenes, serotype M1 strains hold the greatest clinical relevance due to their high prevalence in severe human infections. To enhance our understanding of pathogenesis and discovery of potential therapeutic approaches, we have developed the first genome-scale metabolic model (GEM) for a serotype M1 S. pyogenes strain, which we name iYH543. The curation of iYH543 involved cross-referencing a draft GEM of S. pyogenes serotype M1 from the AGORA2 database with gene essentiality and autotrophy data obtained from transposon mutagenesis-based and growth screens. We achieved a 92.6% (503/543 genes) accuracy in predicting gene essentiality and a 95% (19/20 amino acids) accuracy in predicting amino acid auxotrophy. Additionally, Biolog Phenotype microarrays were employed to examine the growth phenotypes of S. pyogenes, which further contributed to the refinement of iYH543. Notably, iYH543 demonstrated 88% accuracy (168/190 carbon sources) in predicting growth on various sole carbon sources. Discrepancies observed between iYH543 and the actual behavior of living S. pyogenes highlighted areas of uncertainty in the current understanding of S. pyogenes metabolism. iYH543 offers novel insights and hypotheses that can guide future research efforts and ultimately inform novel therapeutic strategies.IMPORTANCEGenome-scale models (GEMs) play a crucial role in investigating bacterial metabolism, predicting the effects of inhibiting specific metabolic genes and pathways, and aiding in the identification of potential drug targets. Here, we have developed the first GEM for the S. pyogenes highly virulent serotype, M1, which we name iYH543. The iYH543 achieved high accuracy in predicting gene essentiality. We also show that the knowledge obtained by substituting actual measurement values for iYH543 helps us gain insights that connect metabolism and virulence. iYH543 will serve as a useful tool for rational drug design targeting S. pyogenes metabolism and computational screening to investigate the interplay between inhibiting virulence factor synthesis and growth.

Characteristics of Corynespora cassiicola, the causal agent of tobacco Corynespora leaf spot, revealed by genomic and metabolic phenomic analysis

Corynespora cassiicola is a highly diverse fungal pathogen that commonly occurs in tropical, subtropical, and greenhouse environments worldwide. In this study, the isolates were identified as C. cassiicola, and the optimum growth and sporulation were studied. The phenotypic characteristics of C. cassiicola, concerning 950 different growth conditions, were tested using Biolog PM plates 1-10. In addition, the strain of C. cassiicola DWZ from tobacco hosts was sequenced for the using Illumina PE150 and Pacbio technologies. The host resistance of tobacco Yunyan 87 with different maturity levels was investigated. In addition, the resistance evaluation of 10 common tobacco varieties was investigated. The results showed that C. cassiicola metabolized 89.47% of the tested carbon source, 100% of the nitrogen source, 100% of the phosphorus source, and 97.14% of the sulfur source. It can adapt to a variety of different osmotic pressure and pH environments, and has good decarboxylase and deaminase activities. The optimum conditions for pathogen growth and sporulation were 25-30 °C, and the growth was better on AEA and OA medium. The total length of the genome was 45.9 Mbp, the GC content was 51.23%, and a total of 13,061 protein-coding genes, 202 non-coding RNAs and 2801 and repeat sequences were predicted. Mature leaves were more susceptible than proper mature and immature leaves, and the average diameter of diseased spots reached 17.74 mm at 12 days. None of the tested ten cultivars exhibited obvious resistance to Corynespora leaf spot of tobacco, whereby all disease spot diameters reached > 10 mm and > 30 mm when at 5 and 10 days after inoculation, respectively. The phenotypic characteristics, genomic analysis of C. cassiicola and the cultivar resistance assessment of this pathogen have increased our understanding of Corynespora leaf spot of tobacco.

Prokaryotic RNA N1-Methyladenosine Erasers Maintain tRNA m1A Modification Levels in Streptomyces venezuelae

tRNA modifications help maintain tRNA structure and facilitate translation and stress response. Found in all three kingdoms of life, m1A tRNA modification occurs in the T loop of many tRNAs, stabilizes tertiary tRNA structure, and impacts translation. M1A in the T loop is reversible by three mammalian demethylase enzymes, which bypasses the need of turning over the tRNA molecule to adjust its m1A levels in cells. However, no prokaryotic tRNA demethylase enzyme has been identified that acts on endogenous RNA modifications. Using Streptomyces venezuelae as a model organism, we confirmed the presence and quantitative m1A tRNA signatures using mass spectrometry and high-throughput tRNA sequencing. We identified two RNA demethylases that can remove m1A in tRNA and validated the activity of a previously annotated tRNA m1A writer. Using single-gene knockouts of these erasers and the m1A writer, we found dynamic changes of m1A levels in many tRNAs under stress conditions. Phenotypic characterization highlighted changes in their growth and altered antibiotic production. Our identification of the first prokaryotic tRNA demethylase enzyme paves the way for investigating new mechanisms of translational regulation in bacteria.

Inhibition of Monilinia fructicola sporulation and pathogenicity through eucalyptol-mediated targeting of MfCat2 by Streptomyces lincolnensis strain JCP1-7

Peach brown rot, attributed to Monilinia fructicola, presents a significant threat to postharvest peach cultivation, causing losses of up to 80%. With an increasing number of countries, spearheaded by the European Union, imposing bans on chemical agents in fruit production, there is a growing interest in mining highly active antibacterial compounds from biological control strains for postharvest disease management. In this study, we highlight the unique ability of Streptomyces lincolnensis strain JCP1-7 to inhibit M. fructicola sporulation, despite its limited antimicrobial efficacy. Through GC-MS analysis, eucalyptol was identified as the key compound. Fumigation of diseased fruits with eucalyptol at a concentration of 0.0335 μg cm-3 demonstrated an in vivo inhibition rate against M. fructicola of 93.13%, completely suppressing spore formation. Transcriptome analysis revealed the impact of eucalyptol on multiple pathogenesis-related pathways, particularly through the inhibition of catalase 2 (Cat2) expression. Experiments with a MfCat2 knockout strain (ΔMfCat2) showed reduced pathogenicity and sensitivity to JCP1-7 and eucalyptol, suggesting MfCat2 as a potential target of JCP1-7 and eucalyptol against M. fructicola. Our findings elucidate that eucalyptol produced by S. lincolnensis JCP1-7 inhibits M. fructicola sporulation by regulating MfCat2, thereby effectively reducing postharvest peach brown rot occurrence. The use of fumigation of eucalyptol offers insights into peach brown rot management on a large scale, thus making a significant contribution to agricultural research.

Biological characteristics and metabolic phenotypes of different anastomosis groups of Rhizoctonia solani strains

BACKGROUND

Rhizoctonia solani is an important plant pathogen worldwide, and causes serious tobacco target spot in tobacco in the last five years. This research studied the biological characteristics of four different anastomosis groups strains (AG-3, AG-5, AG-6, AG-1-IB) of R. solani from tobacco. Using metabolic phenotype technology analyzed the metabolic phenotype differences of these strains.

RESULTS

The results showed that the suitable temperature for mycelial growth of four anastomosis group strains were from 20 to 30oC, and for sclerotia formation were from 20 to 25oC. Under different lighting conditions, R. solani AG-6 strains produced the most sclerotium, followed by R. solani AG-3, R. solani AG-5 and R. solani AG-1-IB. All strains had strong oligotrophic survivability, and can grow on water agar medium without any nitrutions. They exhibited three types of sclerotia distribution form, including dispersed type (R. solani AG-5 and AG-6), peripheral type (R. solani AG-1-IB), and central type (R. solani AG-3). They all presented different pathogenicities in tobacco leaves, with the most virulent was noted by R. solani AG-6, followed by R. solani AG-5 and AG-1-IB, finally was R. solani AG-3. R. solani AG-1-IB strains firstly present symptom after inoculation. Metabolic fingerprints of four anastomosis groups were different to each other. R. solani AG-3, AG-6, AG-5 and AG-1-IB strains efficiently metabolized 88, 94, 71 and 92 carbon substrates, respectively. Nitrogen substrates of amino acids and peptides were the significant utilization patterns for R. solani AG-3. R. solani AG-3 and AG-6 showed a large range of adaptabilities and were still able to metabolize substrates in the presence of the osmolytes, including up to 8% sodium lactate. Four anastomosis groups all showed active metabolism in environments with pH values from 4 to 6 and exhibited decarboxylase activities.

CONCLUSIONS

The biological characteristics of different anastomosis group strains varies, and there were significant differences in the metabolic phenotype characteristics of different anastomosis group strains towards carbon source, nitrogen source, pH, and osmotic pressure.

Genome-scale model of Rothia mucilaginosa predicts gene essentialities and reveals metabolic capabilities

Cystic fibrosis (CF), an inherited genetic disorder caused by mutations in the cystic fibrosis transmembrane conductance regulator gene, results in sticky and thick mucosal fluids. This environment facilitates the colonization of various microorganisms, some of which can cause acute and chronic lung infections, while others may positively impact the disease. Rothia mucilaginosa, an oral commensal, is relatively abundant in the lungs of CF patients. Recent studies have unveiled its anti-inflammatory properties using in vitro three-dimensional lung epithelial cell cultures and in vivo mouse models relevant to chronic lung diseases. Apart from this, R. mucilaginosa has been associated with severe infections. However, its metabolic capabilities and genotype-phenotype relationships remain largely unknown. To gain insights into its cellular metabolism and genetic content, we developed the first manually curated genome-scale metabolic model, iRM23NL. Through growth kinetics and high-throughput phenotypic microarray testings, we defined its complete catabolic phenome. Subsequently, we assessed the model's effectiveness in accurately predicting growth behaviors and utilizing multiple substrates. We used constraint-based modeling techniques to formulate novel hypotheses that could expedite the development of antimicrobial strategies. More specifically, we detected putative essential genes and assessed their effect on metabolism under varying nutritional conditions. These predictions could offer novel potential antimicrobial targets without laborious large-scale screening of knockouts and mutant transposon libraries. Overall, iRM23NL demonstrates a solid capability to predict cellular phenotypes and holds immense potential as a valuable resource for accurate predictions in advancing antimicrobial therapies. Moreover, it can guide metabolic engineering to tailor R. mucilaginosa's metabolism for desired performance.IMPORTANCECystic fibrosis (CF) is a genetic disorder characterized by thick mucosal secretions, leading to chronic lung infections. Rothia mucilaginosa is a common bacterium found in various parts of the human body, acting as a normal part of the flora. In people with weakened immune systems, it can become an opportunistic pathogen, while it is prevalent and active in CF airways. Recent studies have highlighted its anti-inflammatory properties in the lower pulmonary system, indicating the intricate relationship between microbes and human health. Herein, we have developed the first manually curated metabolic model of R. mucilaginosa. Our study examined the previously unknown relationships between the bacterium's genotype and phenotype and identified essential genes that impact the metabolism under various conditions. With this, we opt for paving the way for developing new strategies in antimicrobial therapy and metabolic engineering, leading to enhanced therapeutic outcomes in cystic fibrosis and related conditions.

Metabolic reprogramming during Candida albicans planktonic-biofilm transition is modulated by the transcription factors Zcf15 and Zcf26

Candida albicans is a commensal of the human microbiota that can form biofilms on implanted medical devices. These biofilms are tolerant to antifungals and to the host immune system. To identify novel genes modulating C. albicans biofilm formation, we performed a large-scale screen with 2,454 C. albicans doxycycline-dependent overexpression strains and identified 16 genes whose overexpression significantly hampered biofilm formation. Among those, overexpression of the ZCF15 and ZCF26 paralogs that encode transcription factors and have orthologs only in biofilm-forming species of the Candida clade, caused impaired biofilm formation both in vitro and in vivo. Interestingly, overexpression of ZCF15 impeded biofilm formation without any defect in hyphal growth. Transcript profiling, transcription factor binding, and phenotypic microarray analyses conducted upon overexpression of ZCF15 and ZCF26 demonstrated their role in reprogramming cellular metabolism by regulating central metabolism including glyoxylate and tricarboxylic acid cycle genes. Taken together, this study has identified a new set of biofilm regulators, including ZCF15 and ZCF26, that appear to control biofilm development through their specific role in metabolic remodeling.

High-quality genome assembly and genetic transformation system of Lasiodiplodia theobromae strain LTTK16-3, a fungal pathogen of Chinese hickory

Lasiodiplodia theobromae, as one of the causative agents associated with Chinese hickory trunk cankers, has caused huge economic losses to the Chinese hickory industry. Although the biological characteristics of this pathogen and the occurrence pattern of this disease have been well studied, few studies have addressed the related mechanisms due to the poor molecular and genetic study basis of this fungus. In this study, we sequenced and assembled L. theobromae strain LTTK16-3, isolated from a Chinese hickory tree (cultivar of Linan) in Linan, Zhejiang province, China. Phylogenetic analysis and comparative genomics analysis presented crucial cues in the prediction of LTTK16-3, which shared similar regulatory mechanisms of transcription, DNA replication, and DNA damage response with the other four Chinese hickory trunk canker-associated Botryosphaeria strains including, Botryosphaeria dothidea, Botryosphaeria fabicerciana, Botryosphaeria qingyuanensis, and Botryosphaeria corticis. Moreover, it contained 18 strain-specific protein clusters (not conserved in the other L. theobromae strains, AM2As and CITRA15), with potential roles in specific host-pathogen interactions during the Chinese hickory infection. Additionally, an efficient system for L. theobromae protoplast preparation and polyethylene glycol (PEG) -mediated genetic transformation was firstly established as the foundation for its future mechanisms study. Collectively, the high-quality genome data and the efficient transformation system of L. theobromae here set up the possibility of targeted molecular improvements for Chinese hickory canker control.IMPORTANCEFungi with disparate genomic features are physiologically diverse, possessing species-specific survival strategies and environmental adaptation mechanisms. The high-quality genome data and related molecular genetic studies are the basis for revealing the mechanisms behind the physiological traits that are responsible for their environmental fitness. In this study, we sequenced and assembled the LTTK16-3 strain, the genome of Lasiodiplodia theobromae first obtained from a diseased Chinese hickory tree (cultivar of Linan) in Linan, Zhejiang province, China. Further phylogenetic analysis and comparative genomics analysis provide crucial cues in the prediction of the proteins with potential roles in specific host-pathogen interactions during the Chinese hickory infection. An efficient PEG-mediated genetic transformation system of L. theobromae was established as the foundation for the future mechanisms exploration. The above genetic information and tools set up valuable clues to study L. theobromae pathogenesis and assist in Chinese hickory canker control.

Genome-scale metabolic network model and phenome of solvent-tolerant Pseudomonas putida S12

BACKGROUND

Pseudomonas putida S12 is a gram-negative bacterium renowned for its high tolerance to organic solvents and metabolic versatility, making it attractive for various applications, including bioremediation and the production of aromatic compounds, bioplastics, biofuels, and value-added compounds. However, a metabolic model of S12 has yet to be developed.

RESULTS

In this study, we present a comprehensive and highly curated genome-scale metabolic network model of S12 (iSH1474), containing 1,474 genes, 1,436 unique metabolites, and 2,938 metabolic reactions. The model was constructed by leveraging existing metabolic models and conducting comparative analyses of genomes and phenomes. Approximately 2,000 different phenotypes were measured for S12 and its closely related KT2440 strain under various nutritional and environmental conditions. These phenotypic data, combined with the reported experimental data, were used to refine and validate the reconstruction. Model predictions quantitatively agreed well with in vivo flux measurements and the batch cultivation of S12, which demonstrated that iSH1474 accurately represents the metabolic capabilities of S12. Furthermore, the model was simulated to investigate the maximum theoretical metabolic capacity of S12 growing on toxic organic solvents.

CONCLUSIONS

iSH1474 represents a significant advancement in our understanding of the cellular metabolism of P. putida S12. The combined results of metabolic simulation and comparative genome and phenome analyses identified the genetic and metabolic determinants of the characteristic phenotypes of S12. This study could accelerate the development of this versatile organism as an efficient cell factory for various biotechnological applications.

Syncephalastrum massiliense sp. nov. and Syncephalastrum timoneanum sp. nov. Isolated from Clinical Samples

Mucormycosis is known to be a rare opportunistic infection caused by fungal organisms belonging to the Mucorales order, which includes the Syncephalastrum species. These moulds are rarely involved in clinical diseases and are generally seen as contaminants in clinical laboratories. However, in recent years, case reports of human infections due to Syncephalastrum have increased, especially in immunocompromised hosts. In this study, we described two new Syncephalastrum species, which were isolated from human nails and sputum samples from two different patients. We used several methods for genomic and phenotypic characterisation. The phenotypic analysis relied on the morphological features, analysed both by optical and scanning electron microscopy. We used matrix-assisted laser desorption-ionization time-of-flight mass spectrometry, energy-dispersive X-ray spectroscopy, and BiologTM technology to characterise the proteomic, chemical mapping, and carbon source assimilation profiles, respectively. The genomic analysis relied on a multilocus DNA sequence analysis of the rRNA internal transcribed spacers and D1/D2 large subunit domains, fragments of the translation elongation factor-1 alpha, and the β-tubulin genes. The two novel species in the genus Syncephalastrum, namely S. massiliense PMMF0073 and S. timoneanum PMMF0107, presented a similar morphology: irregular branched and aseptate hyphae with ribbon-like aspects and terminal vesicles at the apices all surrounded by cylindrical merosporangia. However, each species displayed distinct phenotypic and genotypic features. For example, S. timoneanum PMMF0107 was able to assimilate more carbon sources than S. massiliense PMMF0073, such as adonitol, α-methyl-D-glucoside, trehalose, turanose, succinic acid mono-methyl ester, and alaninamide. The polyphasic approach, combining the results of complementary phenotypic and genomic assays, was instrumental for describing and characterising these two new Syncephalastrum species.

Toxic potential assessment of hair dye developer 2,4,5,6-tetraaminopyrimidine sulfate exposed under ambient UVB radiation

Synthetic cosmetics, particularly hair dyes, are becoming increasingly popular among people of all ages and genders. 2,4,5,6-tetraaminopyrimidine sulfate (TAPS) is a key component of oxidative hair dyes and is used as a developer in several hair dyes. TAPS has previously been shown to absorb UVB strongly and degrade in a time-dependent manner, causing phototoxicity in human skin cells. However, the toxic effects of UVB-degraded TAPS are not explored in comparison to parent TAPS. Therefore, this research work aims to assess the toxicity of UVB-degraded TAPS than TAPS on two different test systems, that is, HaCaT (mammalian cell) and Staphylococcus aureus (a bacterial cell). Our result on HaCaT has illustrated that UVB-degraded TAPS is less toxic than parent TAPS. Additionally, UVB-exposed TAPS and parent TAPS were given to S. aureus, and the bacterial growth and their metabolic activity were assessed via CFU and phenotype microarray. The findings demonstrated that parent TAPS reduced bacterial growth via decreased metabolic activity; however, bacteria easily utilized the degraded TAPS. Thus, this study suggests that the products generated after UVB irradiation of TAPS is considered to be safer than their parent TAPS.

Phenotypic Characterization and Draft Genome Sequence Analyses of Two Novel Endospore-Forming Sporosarcina spp. Isolated from Canada Goose (Branta canadensis) Feces

In an attempt to isolate new probiotic bacteria, two Gram-variable, spore-forming, rod-shaped aerobic bacteria designated as strain A4 and A15 were isolated from the feces of Canada geese (Branta canadensis). Strain A4 was able to grow in high salt levels and exhibited lipase activity, while A15 did not propagate under these conditions. Both were positive for starch hydrolysis, and they inhibited the growth of Staphylococcus aureus. The strains of the 16S rRNA sequence shared only 94% similarity to previously identified Sporosarcina spp. The ANI (78.08%) and AAI (82.35%) between the two strains were less than the species threshold. Searches for the most similar genomes using the Mash/Minhash algorithm showed the nearest genome to strain A4 and A15 as Sporosarcina sp. P13 (distance of 21%) and S. newyorkensis (distance of 17%), respectively. Sporosarcina spp. strains A4 and A15 contain urease genes, and a fibronectin-binding protein gene indicates that these bacteria may bind to eukaryotic cells in host gastrointestinal tracts. Phenotypic and phylogenetic data, along with low dDDH, ANI, and AAI values for strains A4 and A15, indicate these bacteria are two novel isolates of the Sporosarcina genus: Sporosarcina sp. A4 sp. nov., type strain as Sporosarcina cascadiensis and Sporosarcina sp. A15 sp. nov., type strain Sporosarcina obsidiansis.

Metabolic interactions affect the biomass of synthetic bacterial biofilm communities

IMPORTANCE

Co-occurrence network analysis is an effective tool for predicting complex networks of microbial interactions in the natural environment. Using isolates from a rhizosphere, we constructed multi-species biofilm communities and investigated co-occurrence patterns between microbial species in genome-scale metabolic models and in vitro experiments. According to our results, metabolic exchanges and resource competition may partially explain the co-occurrence network analysis results found in synthetic bacterial biofilm communities.

Arabinose Plays an Important Role in Regulating the Growth and Sporulation of Bacillus subtilis NCD-2

A microbial fungicide developed from Bacillus subtilis NCD-2 has been registered for suppressing verticillium wilt in crops in China. Spores are the main ingredient of this fungicide and play a crucial role in suppressing plant disease. Therefore, increasing the number of spores of strain NCD-2 during fermentation is important for reducing the cost of the fungicide. In this study, five kinds of carbon sources were found to promote the metabolism of strain NCD-2 revealed via Biolog Phenotype MicroArray (PM) technology. L-arabinose showed the strongest ability to promote the growth and sporulation of strain NCD-2. L-arabinose increased the bacterial concentration and the sporulation efficiency of strain NCD-2 by 2.04 times and 1.99 times compared with D-glucose, respectively. Moreover, L-arabinose significantly decreased the autolysis of strain NCD-2. Genes associated with arabinose metabolism, sporulation, spore resistance to heat, and spore coat formation were significantly up-regulated, and genes associated with sporulation-delaying protein were significantly down-regulated under L-arabinose treatment. The deletion of msmX, which is involved in arabinose transport in the Bacillus genus, decreased growth and sporulation by 53.71% and 86.46% compared with wild-type strain NCD-2, respectively. Complementing the mutant strain by importing an intact msmX gene restored the strain's growth and sporulation.

The EcoCyc Database (2023)

EcoCyc is a bioinformatics database available online at EcoCyc.org that describes the genome and the biochemical machinery of Escherichia coli K-12 MG1655. The long-term goal of the project is to describe the complete molecular catalog of the E. coli cell, as well as the functions of each of its molecular parts, to facilitate a system-level understanding of E. coli. EcoCyc is an electronic reference source for E. coli biologists and for biologists who work with related microorganisms. The database includes information pages on each E. coli gene product, metabolite, reaction, operon, and metabolic pathway. The database also includes information on the regulation of gene expression, E. coli gene essentiality, and nutrient conditions that do or do not support the growth of E. coli. The website and downloadable software contain tools for the analysis of high-throughput data sets. In addition, a steady-state metabolic flux model is generated from each new version of EcoCyc and can be executed online. The model can predict metabolic flux rates, nutrient uptake rates, and growth rates for different gene knockouts and nutrient conditions. Data generated from a whole-cell model that is parameterized from the latest data on EcoCyc are also available. This review outlines the data content of EcoCyc and of the procedures by which this content is generated.

A modular phage vector platform for targeted photodynamic therapy of Gram-negative bacterial pathogens

Growing antibiotic resistance has encouraged the revival of phage-inspired antimicrobial approaches. On the other hand, photodynamic therapy (PDT) is considered a very promising research domain for the protection against infectious diseases. Yet, very few efforts have been made to combine the advantages of both approaches in a modular, retargetable platform. Here, we foster the M13 bacteriophage as a multifunctional scaffold, enabling the selective photodynamic killing of bacteria. We took advantage of the well-defined molecular biology of M13 to functionalize its capsid with hundreds of photo-activable Rose Bengal sensitizers and contemporarily target this light-triggerable nanobot to specific bacterial species by phage display of peptide targeting moieties fused to the minor coat protein pIII of the phage. Upon light irradiation of the specimen, the targeted killing of diverse Gram(-) pathogens occurred at subnanomolar concentrations of the phage vector. Our findings contribute to the development of antimicrobials based on targeted and triggerable phage-based nanobiotherapeutics.

Characteristics of Epicoccum latusicollum as revealed by genomic and metabolic phenomic analysis, the causal agent of tobacco Epicoccus leaf spot

Epicoccum latusicollum is a fungus that causes a severe foliar disease on flue-cured tobacco in southwest China, resulting in significant losses in tobacco yield and quality. To better understand the organism, researchers investigated its optimal growth conditions and metabolic versatility using a combination of traditional methods and the Biolog Phenotype MicroArray technique. The study found that E. latusicollum exhibited impressive metabolic versatility, being able to metabolize a majority of carbon, nitrogen, sulfur, and phosphorus sources tested, as well as adapt to different environmental conditions, including broad pH ranges and various osmolytes. The optimal medium for mycelial growth was alkyl ester agar medium, while oatmeal agar medium was optimal for sporulation, and the optimum temperature for mycelial growth was 25°C. The lethal temperature was 40°C. The study also identified arbutin and amygdalin as optimal carbon sources and Ala-Asp and Ala-Glu as optimal nitrogen sources for E. latusicollum. Furthermore, the genome of E. latusicollum strain T41 was sequenced using Illumina HiSeq and Pacific Biosciences technologies, with 10,821 genes predicted using Nonredundant, Gene Ontology, Clusters of Orthologous Groups, Kyoto Encyclopedia of Genes and Genomes, and SWISS-PROT databases. Analysis of the metabolic functions of phyllosphere microorganisms on diseased tobacco leaves affected by E. latusicollum using the Biolog Eco microplate revealed an inability to efficiently metabolize a total of 29 carbon sources, with only tween 40 showing some metabolizing ability. The study provides new insights into the structure and function of phyllosphere microbiota and highlights important challenges for future research, as well as a theoretical basis for the integrated control and breeding for disease resistance of tobacco Epicoccus leaf spot. This information can be useful in developing new strategies for disease control and management, as well as enhancing crop productivity and quality.

Mechanisms of Regulation of Cryptic Prophage-Encoded Gene Products in Escherichia coli

The dicBF operon of Qin cryptic prophage in Escherichia coli K-12 encodes the small RNA (sRNA) DicF and small protein DicB, which regulate host cell division and are toxic when overexpressed. While new functions of DicB and DicF have been identified in recent years, the mechanisms controlling the expression of the dicBF operon have remained unclear. Transcription from dicBp, the major promoter of the dicBF operon, is repressed by DicA. In this study, we discovered that transcription of the dicBF operon and processing of the polycistronic mRNA is regulated by multiple mechanisms. DicF sRNA accumulates during stationary phase and is processed from the polycistronic dicBF mRNA by the action of both RNase III and RNase E. DicA-mediated transcriptional repression of dicBp can be relieved by an antirepressor protein, Rem, encoded on the Qin prophage. Ectopic production of Rem results in cell filamentation due to strong induction of the dicBF operon, and filamentation is mediated by DicF and DicB. Spontaneous derepression of dicBp occurs in a subpopulation of cells independent of the antirepressor. This phenomenon is reminiscent of the bistable switch of λ phage with DicA and DicC performing functions similar to those of CI and Cro, respectively. Additional experiments demonstrate stress-dependent induction of the dicBF operon. Collectively, our results illustrate that toxic genes carried on cryptic prophages are subject to layered mechanisms of control, some that are derived from the ancestral phage and some that are likely later adaptations. IMPORTANCE Cryptic or defective prophages have lost genes necessary to excise from the bacterial chromosome and produce phage progeny. In recent years, studies have found that cryptic prophage gene products influence diverse aspects of bacterial host cell physiology. However, to obtain a complete understanding of the relationship between cryptic prophages and the host bacterium, identification of the environmental, host, or prophage-encoded factors that induce the expression of cryptic prophage genes is crucial. In this study, we examined the regulation of a cryptic prophage operon in Escherichia coli encoding a small RNA and a small protein that are involved in inhibiting bacterial cell division, altering host metabolism, and protecting the host bacterium from phage infections.

The media composition as a crucial element in high-throughput metabolic network reconstruction

In recent years, metagenome-assembled genomes (MAGs) have provided glimpses into the intra- and interspecies genetic diversity and interactions that form the bases of complex microbial communities. High-throughput reconstruction of genome-scale metabolic networks (GEMs) from MAGs is a promising avenue to disentangle the myriad trophic interactions stabilizing these communities. However, high-throughput reconstruction of GEMs relies on accurate gap filling of metabolic pathways using automated algorithms. Here, we systematically explore how the composition of the media (specification of the available nutrients and metabolites) during gap filling influences the resulting GEMs concerning predicted auxotrophies for fully sequenced model organisms and environmental isolates. We expand this analysis by using 106 MAGs from the same species with differing quality. We find that although the completeness of MAGs influences the fraction of gap-filled reactions, the composition of the media plays the dominant role in the accurate prediction of auxotrophies that form the basis of myriad community interactions. We propose that constraining the media composition for gap filling through both experimental approaches and computational approaches will increase the reliability of high-throughput reconstruction of genome-scale metabolic models from MAGs and paves the way for culture independent prediction of trophic interactions in complex microbial communities.

Vibrio natriegens genome-scale modeling reveals insights into halophilic adaptations and resource allocation

Vibrio natriegens is a Gram-negative bacterium with an exceptional growth rate that has the potential to become a standard biotechnological host for laboratory and industrial bioproduction. Despite this burgeoning interest, the current lack of organism-specific qualitative and quantitative computational tools has hampered the community's ability to rationally engineer this bacterium. In this study, we present the first genome-scale metabolic model (GSMM) of V. natriegens. The GSMM (iLC858) was developed using an automated draft assembly and extensive manual curation and was validated by comparing predicted yields, central metabolic fluxes, viable carbon substrates, and essential genes with empirical data. Mass spectrometry-based proteomics data confirmed the translation of at least 76% of the enzyme-encoding genes predicted to be expressed by the model during aerobic growth in a minimal medium. iLC858 was subsequently used to carry out a metabolic comparison between the model organism Escherichia coli and V. natriegens, leading to an analysis of the model architecture of V. natriegens' respiratory and ATP-generating system and the discovery of a role for a sodium-dependent oxaloacetate decarboxylase pump. The proteomics data were further used to investigate additional halophilic adaptations of V. natriegens. Finally, iLC858 was utilized to create a Resource Balance Analysis model to study the allocation of carbon resources. Taken together, the models presented provide useful computational tools to guide metabolic engineering efforts in V. natriegens.

Cross-protection and cross-feeding between Klebsiella pneumoniae and Acinetobacter baumannii promotes their co-existence

Acinetobacter baumannii and Klebsiella pneumoniae are opportunistic pathogens frequently co-isolated from polymicrobial infections. The infections where these pathogens co-exist can be more severe and recalcitrant to therapy than infections caused by either species alone, however there is a lack of knowledge on their potential synergistic interactions. In this study we characterise the genomes of A. baumannii and K. pneumoniae strains co-isolated from a single human lung infection. We examine various aspects of their interactions through transcriptomic, phenomic and phenotypic assays that form a basis for understanding their effects on antimicrobial resistance and virulence during co-infection. Using co-culturing and analyses of secreted metabolites, we discover the ability of K. pneumoniae to cross-feed A. baumannii by-products of sugar fermentation. Minimum inhibitory concentration testing of mono- and co-cultures reveals the ability for A. baumannii to cross-protect K. pneumoniae against the cephalosporin, cefotaxime. Our study demonstrates distinct syntrophic interactions occur between A. baumannii and K. pneumoniae, helping to elucidate the basis for their co-existence in polymicrobial infections.

Phenotypic and Genomic Difference among Four Botryosphaeria Pathogens in Chinese Hickory Trunk Canker

Botryosphaeria species are amongst the most widespread and important canker and dieback pathogens of trees worldwide, with B. dothidea as one of the most common Botryosphaeria species. However, the information related to the widespread incidence and aggressiveness of B. dothidea among various Botryosphaeria species causing trunk cankers is still poorly investigated. In this study, the metabolic phenotypic diversity and genomic differences of four Chinese hickory canker-related Botryosphaeria pathogens, including B. dothidea, B. qingyuanensis, B. fabicerciana, and B. corticis, were systematically studied to address the competitive fitness of B. dothidea. Large-scale screening of physiologic traits using a phenotypic MicroArray/OmniLog system (PMs) found B. dothidea has a broader spectrum of nitrogen source and greater tolerance toward osmotic pressure (sodium benzoate) and alkali stress among Botryosphaeria species. Moreover, the annotation of B. dothidea species-specific genomic information via a comparative genomics analysis found 143 B. dothidea species-specific genes that not only provides crucial cues in the prediction of B. dothidea species-specific function but also give a basis for the development of a B. dothidea molecular identification method. A species-specific primer set Bd_11F/Bd_11R has been designed based on the sequence of B. dothidea species-specific gene jg11 for the accurate identification of B. dothidea in disease diagnoses. Overall, this study deepens the understanding in the widespread incidence and aggressiveness of B. dothidea among various Botryosphaeria species, providing valuable clues to assist in trunk cankers management.

Vibrio floridensis sp. nov., a novel species closely related to the human pathogen Vibrio vulnificus isolated from a cyanobacterial bloom

A Gram-stain-negative, rod-shaped bacterial strain, designated Vibrio floridensis IRLE0018 (=NRRL B-65642=NCTC 14661), was isolated from a cyanobacterial bloom along the Indian River Lagoon (IRL), a large and highly biodiverse estuary in eastern Florida (USA). The results of phylogenetic, biochemical, and phenotypic analyses indicate that this isolate is distinct from species of the genus Vibrio with validly published names and is the closest relative to the emergent human pathogen, Vibrio vulnificus. Here, we present the complete genome sequence of V. floridensis strain IRLE0018 (4 535 135 bp). On the basis of the established average nucleotide identity (ANI) values for the determination of different species (ANI <95 %), strain IRLE0018, with an ANI of approximately 92 % compared with its closest relative, V. vulnificus, represents a novel species within the genus Vibrio. To our knowledge, this represents the first time this species has been described. The results of genomic analyses of V. floridensis IRLE0018 indicate the presence of antibiotic resistance genes and several known virulence factors, however, its pathogenicity profile (e.g. survival in serum, phagocytosis avoidance) reveals limited virulence potential of this species in contrast to V. vulnificus.

Metabolic phenotype analysis of Trichophyton rubrum after laser irradiation

BACKGROUND

Biological phenotypes are important characteristics of microorganisms, and often reflect their genotype and genotype changes. Traditionally, Trichophyton rubrum (T. rubrum) phenotypes were detected using carbon source assimilation tests, during which the types of tested substances are limited. In addition, the operation is complicated, and only one substance can be tested at once. To observe the changes of the metabolic phenotype of T. rubrum after laser irradiation, a high-throughput phenotype microarray system was used to analyze the metabolism of different carbon, nitrogen, phosphorus and sulfur source substrates in a Biolog metabolic phenotyping system.

RESULTS

The strain of T. rubrum used in this study can effectively utilize 33 carbon, 20 nitrogen, 16 phosphorus, and 13 sulfur source substrates prior to laser irradiation. After laser irradiation, the strain was able to utilize 10 carbon, 12 nitrogen, 12 phosphorus, and 8 sulfur source substrates. The degree of utilization was significantly decreased compared with the control. Both groups efficiently utilized saccharides and organic acids as carbon sources as well as some amino acids as nitrogen sources for growth. The number of substrates utilized by T. rubrum after laser irradiation were significantly reduced, especially carbon substrates. Some substrates utilization degree in the laser treated group was higher than control, such as D-glucosamine, L-glutamine, D-2-Phospho-Glyceric Acid, D-glucosamine-6-phosphate, and D-methionine.

CONCLUSION

Laser irradiation of T. rubrum may lead to changes in the metabolic substrate and metabolic pathway, thus weakening the activity of the strain.

Microbial-Based Products to Control Soil-Borne Pathogens: Methods to Improve Efficacy and to Assess Impacts on Microbiome

Microbial-based products (either as biopesticide or biofertilizers) have a long history of application, though their use is still limited, mainly due to a perceived low and inconsistent efficacy under field conditions. However, their efficacy has always been compared to chemical products, which have a completely different mechanism of action and production process, following the chemical paradigm of agricultural production. This paradigm has also been applied to regulatory processes, particularly for biopesticides, making the marketing of microbial-based formulations difficult. Increased knowledge about bioinocula behavior after application to the soil and their impact on soil microbiome should foster better exploitation of microbial-based products in a complex environment such as the soil. Moreover, the multifunctional capacity of microbial strains with regard to plant growth promotion and protection should also be considered in this respect. Therefore, the methods utilized for these studies are key to improving the knowledge and understanding of microbial-based product activity and improving their efficacy, which, from farmers' point of view, is the parameter to assess the usefulness of a treatment. In this review, we are thus addressing aspects related to the production and formulation process, highlighting the methods that can be used to evaluate the functioning and impact of microbial-based products on soil microbiome, as tools supporting their use and marketing.

Phenotypic analysis and genome sequence of Rhizopus oryzae strain Y5, the causal agent of tobacco pole rot

Rhizopus oryzae is a destructive pathogen that frequently causes tobacco pole rot in curing chambers. Phenotypic characterization of the pathogen was conducted to provide basic biological and pathological information using Biolog Phenotype MicroArray (PM). In addition, the Y5 strain of R. oryzae was sequenced using Illumina HiSeq and Pacific Biosciences (PacBio) technologies. Using PM plates 1-8, 758 growth conditions were tested. Results indicated that R. oryzae could metabolize 54.21% of tested carbon sources, 86.84% of nitrogen sources, 100% of sulfur sources, and 98.31% of phosphorus sources. About 37 carbon compounds, including D-xylose, N-acetyl-D-glucosamine, D-sorbitol, β-methyl-D-glucoside, D-galactose, L-arabinose, and D-cellobiose, significantly supported the growth of the pathogen. PM 3 indicated the active nitrogen sources, including Gly-Asn, Ala-Asp., Ala-Gln, and uric acid. PM 6-8 showed 285 different nitrogen pathways, indicating that different combinations of different amino acids support the growth of the pathogen. Genome sequencing results showed that the R. oryzae Y5 strain had raw data assembled into 2,271 Mbp with an N50 value of 10,563 bp. A genome sequence of 50.3 Mb was polished and assembled into 53 contigs with an N50 length of 1,785,794 bp, maximum contig length of 3,223,184 bp, and a sum of contig lengths of 51,182,778 bp. A total of 12,680 protein-coding genes were predicted using the Nonredundant, Gene Ontology, Clusters of Orthologous Groups, Kyoto Encyclopedia of Genes and Genomes, and SWISS-PROT databases. The genome sequence and annotation resources of R. oryzae provided a reference for studying its biological characteristics, trait-specific genes, pathogen-host interaction, pathogen evolution, and population genetic diversity. The phenomics and genome of R. oryzae will provide insights into microfungal biology, pathogen evolution, and the genetic diversity of epidemics.

High-quality genome-scale metabolic network reconstruction of probiotic bacterium Escherichia coli Nissle 1917

BACKGROUND

Escherichia coli Nissle 1917 (EcN) is a probiotic bacterium used to treat various gastrointestinal diseases. EcN is increasingly being used as a chassis for the engineering of advanced microbiome therapeutics. To aid in future engineering efforts, our aim was to construct an updated metabolic model of EcN with extended secondary metabolite representation.

RESULTS

An updated high-quality genome-scale metabolic model of EcN, iHM1533, was developed based on comparison with 55 E. coli/Shigella reference GEMs and manual curation, including expanded secondary metabolite pathways (enterobactin, salmochelins, aerobactin, yersiniabactin, and colibactin). The model was validated and improved using phenotype microarray data, resulting in an 82.3% accuracy in predicting growth phenotypes on various nutrition sources. Flux variability analysis with previously published ¹³C fluxomics data validated prediction of the internal central carbon fluxes. A standardised test suite called Memote assessed the quality of iHM1533 to have an overall score of 89%. The model was applied by using constraint-based flux analysis to predict targets for optimisation of secondary metabolite production. Modelling predicted design targets from across amino acid metabolism, carbon metabolism, and other subsystems that are common or unique for influencing the production of various secondary metabolites.

CONCLUSION

iHM1533 represents a well-annotated metabolic model of EcN with extended secondary metabolite representation. Phenotype characterisation and the iHM1533 model provide a better understanding of the metabolic capabilities of EcN and will help future metabolic engineering efforts.

Evidence for Complex Interplay between Quorum Sensing and Antibiotic Resistance in Pseudomonas aeruginosa

Quorum sensing (QS) is a cell-density-dependent, intercellular communication system mediated by small diffusible signaling molecules. QS regulates a range of bacterial behaviors, including biofilm formation, virulence, drug resistance mechanisms, and antibiotic tolerance. Enzymes capable of degrading signaling molecules can interfere in QS-a process termed as quorum quenching (QQ). Remarkably, previous work reported some cases where enzymatic interference in QS was synergistic to antibiotics against Pseudomonas aeruginosa. The premise of combination therapy is attractive to fight against multidrug-resistant bacteria, yet comprehensive studies are lacking. Here, we evaluate the effects of QS signal disruption on the antibiotic resistance profile of P. aeruginosa by testing 222 antibiotics and antibacterial compounds from 15 different classes. We found compelling evidence that QS signal disruption does indeed affect antibiotic resistance (40% of all tested compounds; 89/222), albeit not always synergistically (not synergistic for 19% of compounds; 43/222). For some tested antibiotics, such as sulfathiazole and trimethoprim, we were able to relate the changes in resistance caused by QS signal disruption to the modulation of the expression of key genes of the folate biosynthetic pathway. Moreover, using a P. aeruginosa-based Caenorhabditis elegans killing model, we confirmed that enzymatic QQ modulates the effects of antibiotics on P. aeruginosa's pathogenicity in vivo. Altogether, these results show that signal disruption has profound and complex effects on the antibiotic resistance profile of P. aeruginosa. This work suggests that combination therapy including QQ and antibiotics should be discussed not globally but, rather, in case-by-case studies. IMPORTANCE Quorum sensing (QS) is a cell-density-dependent communication system used by a wide range of bacteria to coordinate behaviors. Strategies pertaining to the interference in QS are appealing approaches to control microbial behaviors that depend on QS, including virulence and biofilms. Interference in QS was previously reported to be synergistic with antibiotics, yet no systematic assessment exists. Here, we evaluate the potential of combination treatments using the model opportunistic human pathogen Pseudomonas aeruginosa PA14. In this model, collected data demonstrate that QS largely modulates the antibiotic resistance profile of PA14 (for more than 40% of the tested drugs). However, the outcome of combination treatments is synergistic for only 19% of them. This research demonstrates the complex relationship between QS and antibiotic resistance and suggests that combination therapy including QS inhibitors and antibiotics should be discussed not globally but, rather, in case-by-case studies.

Environmental complexity is more important than mutation in driving the evolution of latent novel traits in E. coli

Recent experiments show that adaptive Darwinian evolution in one environment can lead to the emergence of multiple new traits that provide no immediate benefit in this environment. Such latent non-adaptive traits, however, can become adaptive in future environments. We do not know whether mutation or environment-driven selection is more important for the emergence of such traits. To find out, we evolve multiple wild-type and mutator E. coli populations under two mutation rates in simple (single antibiotic) environments and in complex (multi-antibiotic) environments. We then assay the viability of evolved populations in dozens of new environments and show that all populations become viable in multiple new environments different from those they had evolved in. The number of these new environments increases with environmental complexity but not with the mutation rate. Genome sequencing demonstrates the reason: Different environments affect pleiotropic mutations differently. Our experiments show that the selection pressure provided by an environment can be more important for the evolution of novel traits than the mutational supply experienced by a wild-type and a mutator strain of E. coli.

Novel traits without immediate fitness benefit evolve frequently but we don’t know whether mutation or environment-driven selection drives this evolution. Here, using experimental evolution of E. coli populations, the authors demonstrate the importance of selection in the evolution of latent novel traits.

Coniochaeta massiliensis sp. nov. Isolated from a Clinical Sampl28

The genus Coniochaeta belongs to the class Ascomycota and the family Coniochaetaceae. Some of the Coniochaeta species are plant and animal pathogens, while others are known to be primarily involved in human diseases. In the last few decades, case reports of human infections with Coniochaeta have increased, mainly in immunocompromised hosts. We have described and characterised a new species in the genus Coniochaeta, here named Coniochaeta massiliensis (PMML0158), which was isolated from a clinical sample. Species identification and thorough description were based on apposite and reliable phylogenetic and phenotypic approaches. The phylogenetic methods included multilocus phylogenetic analyses of four genomic regions: ITS (rRNA Internal Transcribed Spacers 1 and 2), TEF-1α (Translation Elongation Factor-1alpha), B-tub2 (β-tubulin2), and D1/D2 domains (28S large subunit rRNA). The phenotypic characterisation consisted, first, of a physiological analysis using both EDX (energy-dispersive X-ray spectroscopy) and Biolog^TM advanced phenotypic technology for fixing the chemical mapping and carbon-source oxidation/assimilation profiles. Afterwards, morphological characteristics were highlighted by optical microscopy and scanning electron microscopy. The in vitro antifungal susceptibility profile was characterised using the E-test^TM exponential gradient method. The molecular analysis revealed the genetic distance between the novel species Coniochaeta massiliensis (PMML0158) and other known taxa, and the phenotypic analysis confirmed its unique chemical and physiological profile when compared with all other species of this genus.

Coastal Transient Niches Shape the Microdiversity Pattern of a Bacterioplankton Population with Reduced Genomes

Globally dominant marine bacterioplankton lineages are often limited in metabolic versatility, owing to their extensive genome reductions, and thus cannot take advantage of transient nutrient patches. It is therefore perplexing how the nutrient-poor bulk seawater sustains the pelagic streamlined lineages, each containing numerous populations. Here, we sequenced the genomes of 33 isolates of the recently discovered CHUG lineage (~2.6 Mbp), which have some of the smallest genomes in the globally abundant Roseobacter group (commonly over 4 Mbp). These genome-reduced bacteria were isolated from a transient habitat: seawater surrounding the brown alga, Sargassum hemiphyllum. Population genomic analyses showed that: (i) these isolates, despite sharing identical 16S rRNA genes, were differentiated into several genetically isolated populations through successive speciation events; (ii) only the first speciation event led to the genetic separation of both core and accessory genomes; and (iii) populations resulting from this event are differentiated at many loci involved in carbon utilization and oxygen respiration, corroborated by BiOLOG phenotype microarray assays and oxygen uptake kinetics experiments, respectively. These differentiated traits match well with the dynamic nature of the macroalgal seawater, in which the quantity and quality of carbon sources and the concentration of oxygen likely vary spatially and temporally, though other habitats, like fresh organic aggregates, cannot be ruled out. Our study implies that transient habitats in the overall nutrient-poor ocean can shape the microdiversity and population structure of genome-reduced bacterioplankton lineages.

Host and microbial-derived metabolites for Clostridioides difficile infection: Contributions, mechanisms and potential applications

Clostridioides difficile infection (CDI), which mostly occurs in hospitalized patients, is the most common and costly health care-associated disease. However, the biology of C. difficile remains incompletely understood. Current therapeutics are still challenged by the frequent recurrence of CDI. Advances in metabolomics facilitate our understanding of the etiology of CDI, which is not merely an alteration in the structure of the gut microbial community but also a dysbiosis metabolic setting promoting the germination, expansion and virulence of C. difficile. Therefore, we summarized the gut microbial and metabolic profiles for CDI under different conditions, such as those of postantibiotic treatment and postfecal microbiota transplantation. The current understanding of the role of host and gut microbial-derived metabolites as well as other nutrients in preventing or alleviating the disease symptoms of CDI will also be provided in this review. We hope that a specific nutrient-centric dietary strategy or the administration of certain nutrients to the colon could serve as an alternate line of investigation for the prophylaxis and mitigation of CDI in the future. Nevertheless, rigorously designed basic studies and randomized controlled trials need to be conducted to assess the functional mechanisms and effects of such therapeutics.

Substrate Utilisation and Energy Metabolism in Non-Growing Campylobacter jejuni M1cam

Campylobacter jejuni, the major cause of bacterial foodborne illness, is also a fastidious organism that requires strict growth requirements in the laboratory. Our aim was to study substrate utilisation and energy metabolism in non-growing C. jejuni to investigate the ability of these bacteria to survive so effectively in the food chain. We integrated phenotypic microarrays and genome-scale metabolic modelling (GSM) to investigate the survival of C. jejuni on 95 substrates. We further investigated the underlying metabolic re-adjustment associated with varying energy demands on each substrate. We identified amino acids, organic acids and H2, as single substrates supporting survival without growth. We identified several different mechanisms, which were used alone or in combination, for ATP production: substrate-level phosphorylation via acetate kinase, the TCA cycle, and oxidative phosphorylation via the electron transport chain that utilised alternative electron donors and acceptors. The benefit of ATP production through each of these mechanisms was associated with the cost of enzyme investment, nutrient availability and/or O2 utilisation. C. jejuni can utilise a wide range of substrates as energy sources, including organic acids commonly used for marination or preservation of ingredients, which might contribute to the success of their survival in changing environments.

A flux-based machine learning model to simulate the impact of pathogen metabolic heterogeneity on drug interactions

Drug combinations are a promising strategy to counter antibiotic resistance. However, current experimental and computational approaches do not account for the entire complexity involved in combination therapy design, such as the effect of pathogen metabolic heterogeneity, changes in the growth environment, drug treatment order, and time interval. To address these limitations, we present a comprehensive approach that uses genome-scale metabolic modeling and machine learning to guide combination therapy design. Our mechanistic approach (a) accommodates diverse data types, (b) accounts for time- and order-specific interactions, and (c) accurately predicts drug interactions in various growth conditions and their robustness to pathogen metabolic heterogeneity. Our approach achieved high accuracy (area under the receiver operating curve (AUROC) = 0.83 for synergy, AUROC = 0.98 for antagonism) in predicting drug interactions for Escherichia coli cultured in 57 metabolic conditions based on experimental validation. The entropy in bacterial metabolic response was predictive of combination therapy outcomes across time scales and growth conditions. Simulation of metabolic heterogeneity using population FBA identified two subpopulations of E. coli cells defined by the levels of three proteins (eno, fadB, and fabD) in glycolysis and lipid metabolism that influence cell tolerance to a broad range of antibiotic combinations. Analysis of the vast landscape of condition-specific drug interactions revealed a set of 24 robustly synergistic drug combinations with potential for clinical use.

Genomic and metabolomic profiling of endolithic Rhodococcus fascians strain S11 isolated from an arid serpentine environment

Genomic and metabolomic studies of endolithic bacteria are essential for understanding their adaptations to extreme conditions of the rock environment and their contributions to mineralization and weathering processes. The endoliths of arid serpentine rocks are exposed to different environmental stresses, including desiccation and re-hydration, temperature fluctuations, oligotrophy, and high concentrations of heavy metals. Bacteria of the genus Rhodococcus commonly inhabit endolithic environments. Here, we describe genomic and metabolomic analyses of the non-pathogenic wild-type Rhodococcus fascians strain S11, isolated from weathered serpentine rock at the arid Khalilovsky massif, Russia. We found that strain S11 lacks the virulence plasmid that functions in the phytopathogenecity of some R. fascians strains. Phenotypic profiling revealed a high pH tolerance, phytase activity and siderophore production. A widely untargeted metabolome analysis performed using an Orbitrap LC-MS/MS method demonstrated the presence of chrysobactin-type siderophores in the culture medium of strain S11. The natural variation of secondary metabolites produced by strain S11 might provide a practical basis for revealing antibacterial, fungicide or insecticidal activities. Finally, plant infection and plant growth stimulation studies showed no observable effect of exposure strain S11 bacteria on the aerial and root parts of Arabidopsis thaliana plants. Based on our findings, R. fascians strain S11 might be promising tool for investigations of organo-mineral interactions, heavy metal bioremediation, and mechanisms of bacterial mediated weathering of plant-free serpentine rock to soil.

In-Human Multiyear Evolution of Carbapenem-Resistant Klebsiella pneumoniae Causing Chronic Colonization and Intermittent Urinary Tract Infections: A Case Study

Carbapenem-resistant Klebsiella pneumoniae (CRKP) is a frequent pathogen of the urinary tract, but how CRKP adapts in vivo over time is unclear. We examined 10 CRKP strains from a patient who experienced chronic colonization and recurrent urinary tract infections over a period of 4.5 years. We performed whole-genome sequencing and phenotypic assays to compare isolates that had evolved relative to the first isolate collected and to correlate genetic and phenotypic changes over time with the meropenem-containing regimen received. Phylogenetic analysis indicated that all 10 strains originated from the same sequence type 258 (ST258) clone and that three sublineages (SL) evolved over time; strains from two dominant sublineages were selected for detailed analysis. Up to 60 new mutations were acquired progressively in genes related to antibiotic resistance, cell metabolism, and biofilm production over time. Doubling of meropenem MICs, increases in biofilm production and bla_KPC expression, and altered carbon metabolism occurred in the latter strains from the last sublineage compared to the initial strain. Subinhibitory meropenem exposure in vitro significantly induced or maintained high levels of biofilm production in colonizing isolates, but isolates causing infection were unaffected. Despite acquiring different mutations that affect carbon metabolism, overall carbon utilization was maintained across different strains. Together, these data showed that isolated urinary CRKP evolved through multiple adaptations affecting carbon metabolism, carbapenem resistance, and biofilm production to support chronic colonization and intermittent urinary tract infections. Our findings highlight the pliability of CRKP in adapting to repeated antibiotic exposure and should be considered when developing novel therapeutic and stewardship strategies. IMPORTANCE Carbapenem-resistant Klebsiella pneumoniae (CRKP) can cause a variety of infections such as recurrent urinary tract infections (rUTI) with the ability to change with the host environment over time. However, it is unclear how CRKP adapts to the urinary tract during chronic infections and colonization. Here, we studied the evolution of CRKP strains from a patient who experienced chronic colonization and recurrent UTIs over a period of 4.5 years despite multiple treatment courses with meropenem-containing regimens. Our findings show the flexibility of CRKP strains in developing changes in carbapenem resistance, biofilm production, and carbon metabolism over time, which could facilitate their persistence in the human body for long periods of time in spite of repeated antibiotic therapy.

Genome-Wide Identification of Novel sRNAs in Streptococcus mutans

Streptococcus mutans is a major pathobiont involved in the development of dental caries. Its ability to utilize numerous sugars and to effectively respond to environmental stress promotes S. mutans proliferation in oral biofilms. Because of their quick action and low energetic cost, noncoding small RNAs (sRNAs) represent an ideal mode of gene regulation in stress response networks, yet their roles in oral pathogens have remained largely unexplored. We identified 15 novel sRNAs in S. mutans and show that they respond to four stress-inducing conditions commonly encountered by the pathogen in human mouth: sugar-phosphate stress, hydrogen peroxide exposure, high temperature, and low pH. To better understand the role of sRNAs in S. mutans, we further explored the function of the novel sRNA SmsR4. Our data demonstrate that SmsR4 regulates the enzyme IIA (EIIA) component of the sorbitol phosphotransferase system, which transports and phosphorylates the sugar alcohol sorbitol. The fine-tuning of EIIA availability by SmsR4 likely promotes S. mutans growth while using sorbitol as the main carbon source. Our work lays a foundation for understanding the role of sRNAs in regulating gene expression in stress response networks in S. mutans and highlights the importance of the underexplored phenomenon of posttranscriptional gene regulation in oral bacteria. IMPORTANCE Small RNAs (sRNAs) are important gene regulators in bacteria, but the identities and functions of sRNAs in Streptococcus mutans, the principal bacterium involved in the formation of dental caries, are unknown. In this study, we identified 15 putative sRNAs in S. mutans and show that they respond to four common stress-inducing conditions present in human mouth: sugar-phosphate stress, hydrogen peroxide exposure, high temperature, and low pH. We further show that the novel sRNA SmsR4 likely modulates sorbitol transport into the cell by regulating SMU_313 mRNA, which encodes the EIIA subunit of the sorbitol phosphotransferase system. Gaining a better understanding of sRNA-based gene regulation may provide new opportunities to develop specific inhibitors of S. mutans growth, thereby improving oral health.

Colletotrichum Spp. Diversity Between Leaf Anthracnose and Crown Rot From the Same Strawberry Plant

Leaf anthracnose (LA) and anthracnose crown rot (ACR) represent serious fungal diseases that pose significant threats to strawberry production. To characterize the pathogen diversity associated with above diseases, 100 strawberry plants, including varieties of "Hongjia," "Zhangji," and "Tianxianzui," were sampled from Jiande and Zhoushan, the primary plantation regions of Zhejiang province, China. A total of 309 Colletotrichum isolates were isolated from crown (150 isolates) and leaves (159 isolates) of affected samples. Among these, 100 isolates obtained from the plants showing both LA and CR symptoms were selected randomly for further characterization. Based on the morphological observations combined with phylogenetic analysis of multiple genes (ACT, ITS, CAL, GAPDH, and CHS), all the 100 tested isolates were identified as C. gloeosporioides species complex, including 91 isolates of C. siamense, 8 isolates of C. fructicola causing both LA and ACR, and one isolate of C. aenigma causing ACR. The phenotypic characteristics of these isolated species were investigated using the BIOLOG phenotype MicroArray (PM) and a total of 950 different metabolic phenotype were tested, showing the characteristics among these isolates and providing the theoretical basis for pathogenic biochemistry and metabolism. The pathogenicity tests showed that even the same Colletotrichum species isolated from different diseased tissues (leaves or crowns) had significantly different pathogenicity toward strawberry leaves and crown. C. siamense isolated from diseased leaves (CSLA) was more aggressive than C. siamense isolated from rotted crown (CSCR) during the infection on "Zhangji" leaves. Additionally, C. fructicola isolated from affected leaf (CFLA) caused more severe symptoms on the leaves of four strawberry varieties compared to C. fructicola isolated from diseased crown (CFCR). For crown rot, the pathogenicity of CSCR was higher than that of CSLA.

Missing Links Between Gene Function and Physiology in Genomics

Knowledge of biological organisms at the molecular level that has been gathered is now organized into databases, often within ontological frameworks. To enable computational comparisons of annotations across different genomes and organisms, controlled vocabularies have been essential, as is the case in the functional annotation classifications used for bacteria, such as MultiFun and the more widely used Gene Ontology. The function of individual gene products as well as the processes in which collections of them participate constitute a wealth of classes that describe the biological role of gene products in a large number of organisms in the three kingdoms of life. In this contribution, we highlight from a qualitative perspective some limitations of these frameworks and discuss challenges that need to be addressed to bridge the gap between annotation as currently captured by ontologies and databases and our understanding of the basic principles in the organization and functioning of organisms; we illustrate these challenges with some examples in bacteria. We hope that raising awareness of these issues will encourage users of Gene Ontology and similar ontologies to be careful about data interpretation and lead to improved data representation.

Microfluidics Microbial Activity MicroAssay: An Automated In Situ Microbial Metabolic Detection System

With no direct extant-life detection instrumentation included in a space mission since the 1970s, the advancement of new technologies to be included in future space missions is imperative. We developed, optimized, and tested a semi-automated prototype, the microfluidics Microbial Activity MicroAssay (μMAMA). This system metabolically characterizes and detects extant microbial life by way of metabolism-indicator redox dyes. We first evaluated the robustness and sensitivity of six redox dye/buffer combinations, and we then tested their responses to metabolic activity in astrobiological analog high-Arctic samples. We determined that the Biolog Inoculating Fluid (IF)-C and AlamarBlue buffered in IF-0a (aB-IF0a) dye/buffer combinations were optimal, as they detected metabolic activity from the fewest microbial cells (10² cells/mL) while maintaining efficacy over a broad physiochemical range of pH (0-13), temperature (-10°C to 37°C), salinity and perchlorate (tested up to 30%), and in the presence of a Mars regolith simulant (MMS-2). The μMAMA, which incorporated these redox dyes, detected extant active cold-adapted microbial life from high Arctic analog sites, including samples amended with substrates targeting chemolithoautotrophic metabolisms. Given μMAMA's small size (we estimate a complete planetary instrument could occupy as little as 3 L) and potential for automation, it could easily be incorporated into almost any landed platform for life detection missions.

Deletion of the N-Terminal Domain of Yeast Eukaryotic Initiation Factor 4B Reprograms Translation and Reduces Growth in Urea

The yeast eukaryotic initiation factor 4B binds the 40S subunit in translation preinitiation complexes (PICs), promoting mRNA recruitment. Recent evidence indicates yeast mRNAs have variable dependence on eIF4B under optimal growth conditions. Given the ability of eIF4B to promote translation as a function of nutrient conditions in mammalian cells, we wondered if eIF4B activities in translation could alter phenotypes in yeast through differential mRNA selection for translation. Here we compared the effects of disrupting yeast eIF4B RNA- and 40S-binding motifs under ∼1400 growth conditions. The RNA-Recognition Motif (RRM) was dispensable for stress responses, but the 40S-binding N-terminal Domain (NTD) promoted growth in response to stressors requiring robust cellular integrity. In particular, the NTD conferred a strong growth advantage in the presence of urea, which may be important for pathogenesis of related fungal species. Ribosome profiling indicated that similar to complete eIF4B deletion, deletion of the NTD dramatically reduced translation, particularly of those mRNAs with long and highly structured 5-prime untranslated regions. This behavior was observed both with and without urea exposure, but the specific mRNA pool associated with ribosomes in response to urea differed. Deletion of the NTD led to relative increases in ribosome association of shorter transcripts with higher dependence on eIF4G, as was noted previously for eIF4B deletion. Gene ontology analysis indicated that proteins encoded by eIF4B NTD-dependent transcripts were associated with the cellular membrane system and the cell wall, while NTD-independent transcripts encoded proteins associated with cytoplasmic proteins and protein synthesis. This analysis highlighted the difference in structure content of mRNAs encoding membrane versus cytoplasmic housekeeping proteins and the variable reliance of specific gene ontology classes on various initiation factors promoting otherwise similar functions. Together our analyses suggest that deletion of the eIF4B NTD prevents cellular stress responses by affecting the capacity to translate a diverse mRNA pool.

Genome-Scale Metabolic Modelling of Lifestyle Changes in Rhizobium leguminosarum

Biological nitrogen fixation in rhizobium-legume symbioses is of major importance for sustainable agricultural practices. To establish a mutualistic relationship with their plant host, rhizobia transition from free-living bacteria in soil to growth down infection threads inside plant roots and finally differentiate into nitrogen-fixing bacteroids. We reconstructed a genome-scale metabolic model for Rhizobium leguminosarum and integrated the model with transcriptome, proteome, metabolome, and gene essentiality data to investigate nutrient uptake and metabolic fluxes characteristic of these different lifestyles. Synthesis of leucine, polyphosphate, and AICAR is predicted to be important in the rhizosphere, while myo-inositol catabolism is active in undifferentiated nodule bacteria in agreement with experimental evidence. The model indicates that bacteroids utilize xylose and glycolate in addition to dicarboxylates, which could explain previously described gene expression patterns. Histidine is predicted to be actively synthesized in bacteroids, consistent with transcriptome and proteome data for several rhizobial species. These results provide the basis for targeted experimental investigation of metabolic processes specific to the different stages of the rhizobium-legume symbioses. IMPORTANCE Rhizobia are soil bacteria that induce nodule formation on plant roots and differentiate into nitrogen-fixing bacteroids. A detailed understanding of this complex symbiosis is essential for advancing ongoing efforts to engineer novel symbioses with cereal crops for sustainable agriculture. Here, we reconstruct and validate a genome-scale metabolic model for Rhizobium leguminosarum bv. viciae 3841. By integrating the model with various experimental data sets specific to different stages of symbiosis formation, we elucidate the metabolic characteristics of rhizosphere bacteria, undifferentiated bacteria inside root nodules, and nitrogen-fixing bacteroids. Our model predicts metabolic flux patterns for these three distinct lifestyles, thus providing a framework for the interpretation of genome-scale experimental data sets and identifying targets for future experimental studies.