Prevalence, spatial structure and evolution of resistance to acetolactate-synthase (ALS) inhibitors and 2,4-D in the major weed Papaver rhoeas (L.) assessed using a massive, country-wide sampling.

BACKGROUND: Corn poppy (Papaver rhoeas) is the most damaging broadleaf weed in France. Massively parallel amplicon sequencing was used to investigate the prevalence, mode of evolution and spread of resistance-endowing ALS alleles in 422 populations randomly sampled throughout poppy's range in France. Bioassays were used to detect resistance to the synthetic auxin 2,4-D in 43 of these populations. RESULTS: A total of 21 100 plants were analysed and 24 mutant ALS alleles carrying an amino-acid substitution involved or potentially involved in resistance were identified. The vast majority (97.6%) of the substitutions occurred at codon Pro197, where all six possible single-nucleotide non-synonymous substitutions plus four double-nucleotide substitutions were identified. Changes observed in the enzymatic properties of the mutant ALS isoforms could not explain the differences in prevalence among the corresponding alleles. Sequence read analysis showed that mutant ALS alleles had multiple, independent evolutionary origins, and could have evolved several times independently within an area of a few kilometres. Finally, 2,4-D resistance was associated with mutant ALS alleles in individual plants in one third of the populations assayed. CONCLUSION: The intricate geographical mosaic of mutant ALS alleles observed is the likely result of the combination of huge population sizes, multiple independent mutation events and human-mediated spread of resistance. Our work highlights the ability of poppy populations and individual plants to accumulate different ALS alleles and as yet unknown mechanisms conferring resistance to synthetic auxins. This does not bode well for the continued use of chemical herbicides to control poppy. © 2023 Society of Chemical Industry.

Effects of sodium nitrite reduction, removal or replacement on cured and cooked meat for microbiological growth, food safety, colon ecosystem, and colorectal carcinogenesis in Fischer 344 rats.

Epidemiological and experimental evidence indicated that processed meat consumption is associated with colorectal cancer risks. Several studies suggest the involvement of nitrite or nitrate additives via N-nitroso-compound formation (NOCs). Compared to the reference level (120 mg/kg of ham), sodium nitrite removal and reduction (90 mg/kg) similarly decreased preneoplastic lesions in F344 rats, but only reduction had an inhibitory effect on Listeria monocytogenes growth comparable to that obtained using the reference nitrite level and an effective lipid peroxidation control. Among the three nitrite salt alternatives tested, none of them led to a significant gain when compared to the reference level: vegetable stock, due to nitrate presence, was very similar to this reference nitrite level, yeast extract induced a strong luminal peroxidation and no decrease in preneoplastic lesions in rats despite the absence of NOCs, and polyphenol rich extract induced the clearest downward trend on preneoplastic lesions in rats but the concomitant presence of nitrosyl iron in feces. Except the vegetable stock, other alternatives were less efficient than sodium nitrite in reducing L. monocytogenes growth.

Urinary Metabolome Analysis Reveals Potential Microbiota Alteration and Electrophilic Burden Induced by High Red Meat Diet: Results from the French NutriNet-Santé Cohort and an In Vivo Intervention Study in Rats.

SCOPE: High red and processed meat consumption is associated with several adverse outcomes such as colorectal cancer and overall global mortality. However, the underlying mechanisms remain debated and need to be elucidated. METHODS AND RESULTS: Urinary untargeted Liquid Chromatography-Mass Spectrometry (LC-MS) metabolomics data from 240 subjects from the French cohort NutriNet-Santé are analyzed. Individuals are matched and divided into three groups according to their consumption of red and processed meat: high red and processed meat consumers, non-red and processed meat consumers, and at random group. Results are supported by a preclinical experiment where rats are fed either a high red meat or a control diet. Microbiota derived metabolites, in particular indoxyl sulfate and cinnamoylglycine, are found impacted by the high red meat diet in both studies, suggesting a modification of microbiota by the high red/processed meat diet. Rat microbiota sequencing analysis strengthens this observation. Although not evidenced in the human study, rat mercapturic acid profile concomitantly reveals an increased lipid peroxidation induced by high red meat diet. CONCLUSION: Novel microbiota metabolites are identified as red meat consumption potential biomarkers, suggesting a deleterious effect, which could partly explain the adverse effects associated with high red and processed meat consumption.

Multiomics Study of Bacterial Growth Arrest in a Synthetic Biology Application.

We investigated the scalability of a previously developed growth switch based on external control of RNA polymerase expression. Our results indicate that, in liter-scale bioreactors operating in fed-batch mode, growth-arrested Escherichia coli cells are able to convert glucose to glycerol at an increased yield. A multiomics quantification of the physiology of the cells shows that, apart from acetate production, few metabolic side effects occur. However, a number of specific responses to growth slow-down and growth arrest are launched at the transcriptional level. These notably include the downregulation of genes involved in growth-associated processes, such as amino acid and nucleotide metabolism and translation. Interestingly, the transcriptional responses are buffered at the proteome level, probably due to the strong decrease of the total mRNA concentration after the diminution of transcriptional activity and the absence of growth dilution of proteins. Growth arrest thus reduces the opportunities for dynamically adjusting the proteome composition, which poses constraints on the design of biotechnological production processes but may also avoid the initiation of deleterious stress responses.

Identification of copy number variation in French dairy and beef breeds using next-generation sequencing.

BACKGROUND: Copy number variations (CNV) are known to play a major role in genetic variability and disease pathogenesis in several species including cattle. In this study, we report the identification and characterization of CNV in eight French beef and dairy breeds using whole-genome sequence data from 200 animals. Bioinformatics analyses to search for CNV were carried out using four different but complementary tools and we validated a subset of the CNV by both in silico and experimental approaches. RESULTS: We report the identification and localization of 4178 putative deletion-only, duplication-only and CNV regions, which cover 6% of the bovine autosomal genome; they were validated by two in silico approaches and/or experimentally validated using array-based comparative genomic hybridization and single nucleotide polymorphism genotyping arrays. The size of these variants ranged from 334 bp to 7.7 Mb, with an average size of ~ 54 kb. Of these 4178 variants, 3940 were deletions, 67 were duplications and 171 corresponded to both deletions and duplications, which were defined as potential CNV regions. Gene content analysis revealed that, among these variants, 1100 deletions and duplications encompassed 1803 known genes, which affect a wide spectrum of molecular functions, and 1095 overlapped with known QTL regions. CONCLUSIONS: Our study is a large-scale survey of CNV in eight French dairy and beef breeds. These CNV will be useful to study the link between genetic variability and economically important traits, and to improve our knowledge on the genomic architecture of cattle.

Identification and Characterization of the Dermal Panniculus Carnosus Muscle Stem Cells.

The dermal Panniculus carnosus (PC) muscle is important for wound contraction in lower mammals and represents an interesting model of muscle regeneration due to its high cell turnover. The resident satellite cells (the bona fide muscle stem cells) remain poorly characterized. Here we analyzed PC satellite cells with regard to developmental origin and purported function. Lineage tracing shows that they originate in Myf5(+), Pax3/Pax7(+) cell populations. Skin and muscle wounding increased PC myofiber turnover, with the satellite cell progeny being involved in muscle regeneration but with no detectable contribution to the wound-bed myofibroblasts. Since hematopoietic stem cells fuse to PC myofibers in the absence of injury, we also studied the contribution of bone marrow-derived cells to the PC satellite cell compartment, demonstrating that cells of donor origin are capable of repopulating the PC muscle stem cell niche after irradiation and bone marrow transplantation but may not fully acquire the relevant myogenic commitment.

CAZyChip: dynamic assessment of exploration of glycoside hydrolases in microbial ecosystems.

BACKGROUND: Microorganisms constitute a reservoir of enzymes involved in environmental carbon cycling and degradation of plant polysaccharides through their production of a vast variety of Glycoside Hydrolases (GH). The CAZyChip was developed to allow a rapid characterization at transcriptomic level of these GHs and to identify enzymes acting on hydrolysis of polysaccharides or glycans. RESULTS: This DNA biochip contains the signature of 55,220 bacterial GHs available in the CAZy database. Probes were designed using two softwares, and microarrays were directly synthesized using the in situ ink-jet technology. CAZyChip specificity and reproducibility was validated by hybridization of known GHs RNA extracted from recombinant E. coli strains, which were previously identified by a functional metagenomic approach. The GHs arsenal was also studied in bioprocess conditions using rumen derived microbiota. CONCLUSIONS: The CAZyChip appears to be a user friendly tool for profiling the expression of a large variety of GHs. It can be used to study temporal variations of functional diversity, thereby facilitating the identification of new efficient candidates for enzymatic conversions from various ecosystems.

Meiotic pairing and gene expression disturbance in germ cells from an infertile boar with a balanced reciprocal autosome-autosome translocation.

Individuals carrying balanced constitutional reciprocal translocations generally have a normal phenotype, but often present reproductive disorders. The aim of our research was to analyze the meiotic process in an oligoasthenoteratospermic boar carrying an asymmetric reciprocal translocation involving chromosomes 1 and 14. Different multivalent structures (quadrivalent and trivalent plus univalent) were identified during chromosome pairing analysis. Some of these multivalents were characterized by the presence of unpaired autosomal segments with histone γH2AX accumulation sometimes associated with the XY body. Gene expression in spermatocytes was studied by RNA-DNA-FISH and microarray-based testis transcriptome analysis. Our results revealed a decrease in gene expression for chromosomes 1 and 14 and an up-regulated expression of X-chromosome genes for the translocated boar compared with normal individuals. We hypothesized that the observed meiotic arrest and reproductive failure in this boar might be due to silencing of crucial autosomal genes (MSUC) and disturbance of meiotic sex chromosome inactivation (MSCI). Further analysis revealed abnormal meiotic recombination (frequency and distribution) and the production of a high rate of unbalanced spermatozoa.

Exploring transcriptomic diversity in muscle revealed that cellular signaling pathways mainly differentiate five Western porcine breeds.

BACKGROUND: Among transcriptomic studies, those comparing species or populations can increase our understanding of the impact of the evolutionary forces on the differentiation of populations. A particular situation is the one of short evolution time with breeds of a domesticated species that underwent strong selective pressures. In this study, the gene expression diversity across five pig breeds has been explored in muscle. Samples came from: 24 Duroc, 33 Landrace, 41 Large White dam line, 10 Large White sire line and 39 Piétrain. From these animals, 147 muscle samples obtained at slaughter were analyzed using the porcine Agilent 44 K v1 microarray. RESULTS: A total of 12,358 genes were identified as expressed in muscle after normalization and 1,703 genes were declared differential for at least one breed (FDR < 0.001). The functional analysis highlighted that gene expression diversity is mainly linked to cellular signaling pathways such as the PI3K (phosphoinositide 3-kinase) pathway. The PI3K pathway is known to be involved in the control of development of the skeletal muscle mass by affecting extracellular matrix - receptor interactions, regulation of actin cytoskeleton pathways and some metabolic functions. This study also highlighted 228 spots (171 unique genes) that differentiate the breeds from each other. A common subgroup of 15 genes selected by three statistical methods was able to differentiate Duroc, Large White and Piétrain breeds. CONCLUSIONS: This study on transcriptomic differentiation across Western pig breeds highlighted a global picture: mainly signaling pathways were affected. This result is consistent with the selection objective of increasing muscle mass. These transcriptional changes may indicate selection pressure or simply breed differences which may be driven by human selection. Further work aiming at comparing genetic and transcriptomic diversities would further increase our understanding of the consequences of human impact on livestock species.

Fuzzy logic selection as a new reliable tool to identify molecular grade signatures in breast cancer--the INNODIAG study.

BACKGROUND: Personalized medicine has become a priority in breast cancer patient management. In addition to the routinely used clinicopathological characteristics, clinicians will have to face an increasing amount of data derived from tumor molecular profiling. The aims of this study were to develop a new gene selection method based on a fuzzy logic selection and classification algorithm, and to validate the gene signatures obtained on breast cancer patient cohorts. METHODS: We analyzed data from four published gene expression datasets for breast carcinomas. We identified the best discriminating genes by comparing molecular expression profiles between histologic grade 1 and 3 tumors for each of the training datasets. The most pertinent probes were selected and used to define fuzzy molecular grade 1-like (good prognosis) and fuzzy molecular grade 3-like (poor prognosis) profiles. To evaluate the prognostic performance of the fuzzy grade signatures in breast cancer tumors, a Kaplan-Meier analysis was conducted to compare the relapse-free survival deduced from histologic grade and fuzzy molecular grade classification. RESULTS: We applied the fuzzy logic selection on breast cancer databases and obtained four new gene signatures. Analysis in the training public sets showed good performance of these gene signatures for grade (sensitivity from 90% to 95%, specificity 67% to 93%). To validate these gene signatures, we designed probes on custom microarrays and tested them on 150 invasive breast carcinomas. Good performance was obtained with an error rate of less than 10%. For one gene signature, among 74 histologic grade 3 and 18 grade 1 tumors, 88 cases (96%) were correctly assigned. Interestingly histologic grade 2 tumors (n = 58) were split in these two molecular grade categories. CONCLUSION: We confirmed the use of fuzzy logic selection as a new tool to identify gene signatures with good reliability and increased classification power. This method based on artificial intelligence algorithms was successfully applied to breast cancers molecular grade classification allowing histologic grade 2 classification into grade 1 and grade 2 like to improve patients prognosis. It opens the way to further development for identification of new biomarker combinations in other applications such as prediction of treatment response.

Phytochip: development of a DNA-microarray for rapid and accurate identification of Pseudo-nitzschia spp and other harmful algal species.

Detection of harmful algal blooms has become a challenging concern because of the direct impacts on public health and economy. The identification of toxic dinoflagellates and diatoms in monitoring programs requires an extensive taxonomic expertise and is time consuming. Advances in molecular biology have allowed the development of new approaches, more rapid, accurate and cost-effective for detecting these microorganisms. In this context, we developed a new DNA microarray (called, Phytochip) for the simultaneous detection of multiple HAB species with a particular emphasis on Pseudo-nitzschia species. Oligonucleotide probes were designed along the rRNA operon. After DNA extraction, the target rDNA genes were amplified and labeled using an asymmetric PCR; then, the amplicons were hybridized to the oligonucleotide probes present on the chips. The total assay from seawater sampling to data acquisition can be performed within a working day. Specificity and sensitivity were assessed by using monoclonal cultures, mixtures of species and field samples spiked with a known amount of cultured cells. The Phytochip with its 81 validated oligonucleotide probes was able to detect 12 species of Pseudo-nitzschia and 11 species of dinoflagellates among which were 3 species of Karenia and 3 species of Alexandrium. The Phytochip was applied to environmental samples already characterized by light microscopy and cloned into DNA libraries. The hybridizations on the Phytochip were in good agreement with the sequences retrieved from the clone libraries and the microscopic observations. The Phytochip enables a reliable multiplex detection of phytoplankton and can assist a water quality monitoring program as well as more general ecological research.

Exposure to high static or pulsed magnetic fields does not affect cellular processes in the yeast Saccharomyces cerevisiae.

We report results of a study of the effects of strong static (up to 16 T for 8 h) and pulsed (up to 55 T single-shot and 4 x 20 T repeated shots) magnetic fields on Saccharomyces cerevisiae cultures in the exponential phase of growth. In contrast to previous reports restricted to only a limited number of cellular parameters, we have examined a wide variety of cellular processes: genome-scale gene expression, proteome profile, cell viability, morphology, and growth, metabolic and fermentation activity after magnetic field exposure. None of these cellular activities were impaired in response to static or pulsed magnetic field exposure. Our results confirm and extend previous reports on the absence of magnetic field effects on yeast and support the hypothesis that magnetic fields have no impact on the transcriptional machinery and on the integrity of unicellular biological systems.

Detection of minority variants within bovine respiratory syncytial virus populations using oligonucleotide-based microarrays.

Microarray technology, originally developed for highly parallel examination of gene expression is regarded as a potential tool in prognosis and diagnosis. With respect to a discrimination analysis, difference as small as one nucleotide base can be distinguished using oligonucleotide-based microarrays. However, this degree of specificity is dependent on several parameters, including the size of the oligoprobes and the sequence context of the probes (e.g. local melting temperature), hybridization conditions and to some extent the chemistry of the glass slides onto which the probes are deposited. Using bovine respiratory syncytial virus (BRSV) as a model study, an oligonucleotide-based microarray approach was developed to measure the relative abundance of a particular single nucleotide variant within mixed BRSV populations. Using this technology, we show that it is possible to discriminate at a rate of 1%, minority variants in a BRSV population.