Pivotal functions and impact of long con-coding RNAs on cellular processes and genome integrity.

Recent advances in uncovering the mysteries of the human genome suggest that long non-coding RNAs (lncRNAs) are important regulatory components. Although lncRNAs are known to affect gene transcription, their mechanisms and biological implications are still unclear. Experimental research has shown that lncRNA synthesis, subcellular localization, and interactions with macromolecules like DNA, other RNAs, or proteins can all have an impact on gene expression in various biological processes. In this review, we highlight and discuss the major mechanisms through which lncRNAs function as master regulators of the human genome. Specifically, the objective of our review is to examine how lncRNAs regulate different processes like cell division, cell cycle, and immune responses, and unravel their roles in maintaining genomic architecture and integrity.

Statistical Optimization and Partial Characterization of Xylanases Produced by Streptomyces sp. S1M3I Using Olive Pomace as a Fermentation Substrate.

Xylanase production by Streptomyces sp. S1M3I was optimized by response surface methodology (RSM), followed by a partial characterization of these enzymes. Olive pomace was used as a substrate for growing Streptomyces sp. S1M3I in submerged fermentation. Effects of incubation time, pH, temperature, carbon source, nitrogen source, and inoculum size on xylanase production were studied, through the one-factor-at-a-time method. Then, a 33-factorial experimental design with RSM and the Box-Behnken design was investigated for the major influence factors. Maximum xylanase production (11.28 U/mL) was obtained when the strain was grown in mineral medium supplemented with 3% (w/v) of olive pomace powder and 0.3% (w/v) of ammonium sulfate, at a pH 7.4 and an incubation temperature of 40 °C. The xylanases in the supernatant degraded all tested substrates, with higher activity for the low-viscosity wheat arabinoxylan substrate. Two xylanases with close molecular masses were detected by zymogram analysis: Xyl-1 and Xyl-2 with molecular masses of 24.14 kDa and 27 kDa, respectively. The optimization of enzyme production parameters of Streptomyces sp. S1M3I and the characterization of these enzymes are prerequisites to enhancing xylanase production yield, which is crucial for further biotechnological processes.

Integration of data-independent acquisition (DIA) with co-fractionation mass spectrometry (CF-MS) to enhance interactome mapping capabilities.

Proteomics technologies are continually advancing, providing opportunities to develop stronger and more robust protein interaction networks (PINs). In part, this is due to the ever-growing number of high-throughput proteomics methods that are available. This review discusses how data-independent acquisition (DIA) and co-fractionation mass spectrometry (CF-MS) can be integrated to enhance interactome mapping abilities. Furthermore, integrating these two techniques can improve data quality and network generation through extended protein coverage, less missing data, and reduced noise. CF-DIA-MS shows promise in expanding our knowledge of interactomes, notably for non-model organisms (NMOs). CF-MS is a valuable technique on its own, but upon the integration of DIA, the potential to develop robust PINs increases, offering a unique approach for researchers to gain an in-depth understanding into the dynamics of numerous biological processes.

Review of the Real and Sometimes Hidden Costs in Proteomics Experimental Workflows.

A typical proteomics workflow covers all the steps from growing or collecting the cells/tissues/organism, protein extraction, digestion and cleanup, mass spectrometric analysis, and, finally, extensive bioinformatics to derive biological insight from the data. The details of the procedures employed for this can vary widely by laboratory and by sample type: e.g., hard tissues or cells with walls require much more mechanical disruption to extract proteins than do soft tissues, biological fluids, or wall-less cells. Everything then converges on the mass spectrometer, where there are further choices to be made about how to do the analysis. There is one commonality, however, virtually every group around the world now uses liquid chromatography on-line coupled to tandem mass spectrometry, which means that significant amounts of instrument time are dedicated to every sample. There are many other reviews or methods papers, including in this volume, that cover the details of the various procedures involved in proteomic analyses of all types of samples. Our focus here will be on the cost considerations for such analyses, including considerations to ensure that useful data can be obtained the first time a sample is analyzed. Some of these costs are often overlooked, particularly for those groups who operate their own mass spectrometer(s) and do not have to go to a fee-for-service facility to have something analyzed. The chapter presents several challenges and key suggestions in proving hypotheses in proteomics experimental workflow in different biological systems with specific regard to the costs involved, both real and hidden. The detailed methodology for cost-based studies reported in this chapter can help researchers to set up their laboratory with appropriate equipment as well as to identify potential collaborations based on their analytical instrumentation.

Cellulase-Hemicellulase Activities and Bacterial Community Composition of Different Soils from Algerian Ecosystems.

Soil microorganisms are important mediators of carbon cycling in nature. Although cellulose- and hemicellulose-degrading bacteria have been isolated from Algerian ecosystems, the information on the composition of soil bacterial communities and thus the potential of their members to decompose plant residues is still limited. The objective of the present study was to describe and compare the bacterial community composition in Algerian soils (crop, forest, garden, and desert) and the activity of cellulose- and hemicellulose-degrading enzymes. Bacterial communities were characterized by high-throughput 16S amplicon sequencing followed by the in silico prediction of their functional potential. The highest lignocellulolytic activity was recorded in forest and garden soils whereas activities in the agricultural and desert soils were typically low. The bacterial phyla Proteobacteria (in particular classes α-proteobacteria, δ-proteobacteria, and γ-proteobacteria), Firmicutes, and Actinobacteria dominated in all soils. Forest and garden soils exhibited higher diversity than agricultural and desert soils. Endocellulase activity was elevated in forest and garden soils. In silico analysis predicted higher share of genes assigned to general metabolism in forest and garden soils compared with agricultural and arid soils, particularly in carbohydrate metabolism. The highest potential of lignocellulose decomposition was predicted for forest soils, which is in agreement with the highest activity of corresponding enzymes.

Efficient screening of potential cellulases and hemicellulases produced by Bosea sp. FBZP-16 using the combination of enzyme assays and genome analysis.

Identification of bacteria that produce carbohydrolytic enzymes is extremely important given the increased demand for these enzymes in many industries. Twenty lignocellulose-degrading bacterial isolates from Algerian compost and different soils were screened for their potential to produce different enzymes involved in biomass deconstruction. Based on 16S rRNA gene sequencing, the isolates belonged to Proteobacteria and Actinobacteria. Differences among species were reflected both as the presence/absence of enzymes or at the level of enzyme activity. Among the most active species, Bosea sp. FBZP-16 demonstrated cellulolytic activity on both amorphous cellulose (CMC) and complex lignocellulose (wheat straw) and was selected for whole-genomic sequencing. The genome sequencing revealed the presence of a complex enzymatic machinery required for organic matter decomposition. Analysis of the enzyme-encoding genes indicated that multiple genes for endoglucanase, xylanase, ß-glucosidase and ß-mannosidase are present in the genome with enzyme activities displayed by the bacterium, while other enzymes, such as certain cellobiohydrolases, were not detected at the genomic level. This indicates that a combination of functional screening of bacterial cultures with the use of genome-derived information is important for the prediction of potential enzyme production. These results provide insight into their possible exploitation for the production of fuels and chemicals derived from plant biomass.