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RNA-Seq is a widely used technology that allows an efficient genome-wide quantification of gene expressions for, for example, differential expression (DE) analysis. After a brief review of the main issues, methods and tools related to the DE analysis of RNA-Seq data, this article focuses on the impact of both the replicate number and library size in such analyses. While the main drawback of previous relevant studies is the lack of generality, we conducted both an analysis of a two-condition experiment (with eight biological replicates per condition) to compare the results with previous benchmark studies, and a meta-analysis of 17 experiments with up to 18 biological conditions, eight biological replicates and 100 million (M) reads per sample. As a global trend, we concluded that the replicate number has a larger impact than the library size on the power of the DE analysis, except for low-expressed genes, for which both parameters seem to have the same impact. Our study also provides new insights for practitioners aiming to enhance their experimental designs. For instance, by analyzing both the sensitivity and specificity of the DE analysis, we showed that the optimal threshold to control the false discovery rate (FDR) is approximately 2 , where r is the replicate number. Furthermore, we showed that the false positive rate (FPR) is rather well controlled by all three studied R packages: , and . We also analyzed the impact of both the replicate number and library size on gene ontology (GO) enrichment analysis. Interestingly, we concluded that increases in the replicate number and library size tend to enhance the sensitivity and specificity, respectively, of the GO analysis. Finally, we recommend to RNA-Seq practitioners the production of a pilot data set to strictly analyze the power of their experimental design, or the use of a public data set, which should be similar to the data set they will obtain. For individuals working on tomato research, on the basis of the meta-analysis, we recommend at least four biological replicates per condition and 20 M reads per sample to be almost sure of obtaining about 1000 DE genes if they exist.

Plastic production reached 400 million tons in 2022 (ref. 1), with packaging and single-use plastics accounting for a substantial amount of this2. The resulting waste ends up in landfills, incineration or the environment, contributing to environmental pollution3. Shifting to biodegradable and compostable plastics is increasingly being considered as an efficient waste-management alternative4. Although polylactide (PLA) is the most widely used biosourced polymer5, its biodegradation rate under home-compost and soil conditions remains low6-8. Here we present a PLA-based plastic in which an optimized enzyme is embedded to ensure rapid biodegradation and compostability at room temperature, using a scalable industrial process. First, an 80-fold activity enhancement was achieved through structure-based rational engineering of a new hyperthermostable PLA hydrolase. Second, the enzyme was uniformly dispersed within the PLA matrix by means of a masterbatch-based melt extrusion process. The liquid enzyme formulation was incorporated in polycaprolactone, a low-melting-temperature polymer, through melt extrusion at 70 °C, forming an 'enzymated' polycaprolactone masterbatch. Masterbatch pellets were integrated into PLA by melt extrusion at 160 °C, producing an enzymated PLA film (0.02% w/w enzyme) that fully disintegrated under home-compost conditions within 20-24 weeks, meeting home-composting standards. The mechanical and degradation properties of the enzymated film were compatible with industrial packaging applications, and they remained intact during long-term storage. This innovative material not only opens new avenues for composters and biomethane production but also provides a feasible industrial solution for PLA degradation.

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.

Due to organ shortage, clinicians are prone to consider alternative type of organ donors among them donors deceased after circulatory death (DCD). However, especially using these organs which are more prone to graft dysfunction, there is a need to better understand mechanistic events ocuring during ischemia phase and leading to ischemia/reperfusion injuries (IRI). The aim of this study is to provide a dynamic transcriptomic analysis of preclinical porcine model kidneys subjected to ischemic stress mimicking DCD donor. We compared cortex and corticomedullary junction (CMJ) tissues from porcine kidneys submitted to 60 min warm ischemia (WI) followed by 0, 6 or 24 hours of cold storage in University of Wisconsin solution versus control non-ischemic kidneys (n = 5 per group). 29 cortex genes and 113 CMJ genes were significantly up or down-regulated after WI versus healthy kidneys, and up to 400 genes were regulated after WI followed by 6 or 24 hours of cold storage (p < 0.05). Functionnal enrichment analysis (home selected gene kinetic classification, Gene-ontology-biological processes and Gene-ontology-molecular-function) revealed relevant genes implication during WI and cold storage. We uncovered targets which we will further validate as biomarkers and new therapeutic targets to optimize graft kidney quality before transplantation and improve whole transplantation outcome.

Wine produced at low temperature is often considered to have improved sensory qualities. To investigate the effects of temperature on winemaking, the expression patterns during the industrial fermentation process carried out at 13 1C and 25 1C were compared, and correlated with physiological and biochemical data, including viability, fermentation byproducts and lipid content of the cells. From a total of 535 ORFs that were significantly differentially expressed between the 13 1C and 25 1C fermentations, two significant transcription programmes were identified. A cold-stress response was expressed at the initial stage of the fermentation, and this was followed by a transcription pattern of upregulated genes concerned with the cell cycle, growth control and maintenance in the middle and late stages of the process at 13 1C with respect to 25 1C. These expression patterns were correlated with higher cell viability at low temperature. The other relevant transcriptomic difference was that several genes implicated in cytosolic fatty acid synthesis were downregulated, while those involved in mitochondrial short-chain fatty acid synthesis were upregulated in the fermentation process conducted at 13 1C with respect to that at 25 1C. These transcriptional changes were qualitatively correlated with improved resistance to ethanol and increased production of short-chain (C 4-C 8) fatty acids and their corresponding esters at 13 1C as compared to 25 1C. While this increase of ethyl esters may account in part for the improved sensory quality of wine fermented at 13 1C, it is still unclear how the esterification of the short-chain fatty acids takes place. On the basis of its strong upregulation at 13 1C, we propose a possible role of IAH1 encoding an esterase/ester synthase in this process.

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.

In bacteria, faithful DNA segregation of chromosomes and plasmids is mainly mediated by ParABS systems. These systems, consisting of a ParA ATPase, a DNA binding ParB CTPase, and centromere sites parS, orchestrate the separation of newly replicated DNA copies and their intracellular positioning. Accurate segregation relies on the assembly of a high-molecular-weight complex, comprising a few hundreds of ParB dimers nucleated from parS sites. This complex assembles in a multi-step process and exhibits dynamic liquid-droplet properties. Despite various proposed models, the complete mechanism for partition complex assembly remains elusive. This study investigates the impact of DNA supercoiling on ParB DNA binding profiles in vivo, using the ParABS system of the plasmid F. We found that variations in DNA supercoiling does not significantly affect any steps in the assembly of the partition complex. Furthermore, physical modeling, leveraging ChIP-seq data from linear plasmids F, suggests that ParB sliding is restricted to approximately 2-Kbp from parS, highlighting the necessity for additional mechanisms beyond ParB sliding over DNA for concentrating ParB into condensates nucleated at parS. Lastly, explicit simulations of a polymer coated with bound ParB suggest a dominant role for ParB-ParB interactions in DNA compaction within ParB condensates.

Wine produced at low temperature is often considered to have improved sensory qualities. To investigate the effects of temperature on winemaking, the expression patterns during the industrial fermentation process carried out at 13 1C and 25 1C were compared, and correlated with physiological and biochemical data, including viability, fermentation byproducts and lipid content of the cells. From a total of 535 ORFs that were significantly differentially expressed between the 13 1C and 25 1C fermentations, two significant transcription programmes were identified. A cold-stress response was expressed at the initial stage of the fermentation, and this was followed by a transcription pattern of upregulated genes concerned with the cell cycle, growth control and maintenance in the middle and late stages of the process at 13 1C with respect to 25 1C. These expression patterns were correlated with higher cell viability at low temperature. The other relevant transcriptomic difference was that several genes implicated in cytosolic fatty acid synthesis were downregulated, while those involved in mitochondrial short-chain fatty acid synthesis were upregulated in the fermentation process conducted at 13 1C with respect to that at 25 1C. These transcriptional changes were qualitatively correlated with improved resistance to ethanol and increased production of short-chain (C 4-C 8) fatty acids and their corresponding esters at 13 1C as compared to 25 1C. While this increase of ethyl esters may account in part for the improved sensory quality of wine fermented at 13 1C, it is still unclear how the esterification of the short-chain fatty acids takes place. On the basis of its strong upregulation at 13 1C, we propose a possible role of IAH1 encoding an esterase/ester synthase in this process.

Chromosome and plasmid segregation in bacteria are mostly driven by ParABS systems. These DNA partitioning machineries rely on large nucleoprotein complexes assembled on centromere sites (parS). However, the mechanism of how a few parS-bound ParB proteins nucleate the formation of highly concentrated ParB clusters remains unclear despite several proposed physico-mathematical models. We discriminated between these different models by varying some key parameters in vivo using the plasmid F partition system. We found that \"Nucleation & caging\" is the only coherent model recapitulating in vivo data. We also showed that the stochastic self-assembly of partition complexes (i) does not directly involve ParA, (ii) results in a dynamic structure of discrete size independent of ParB concentration, and (iii) is not perturbed by active transcription but is by protein complexes. We refined the \"Nucleation & caging\" model and successfully applied it to the chromosomally-encoded Par system of Vibrio cholerae, indicating that this stochastic self-assembly mechanism is widely conserved from plasmids to chromosomes.