Deep sequencing approaches for the analysis of prokaryotic transcriptional boundaries and dynamics

A Role of Multi-Omics Technologies in Sheep and Goat Meats: Progress and Way Ahead

Sheep and goat meats are increasingly popular worldwide due to their superior nutritional properties and distinctive flavor profiles. In recent decades, substantial progress in meat science has facilitated in-depth examinations of ovine and caprine muscle development during the antemortem phase, as well as post-mortem changes influencing meat attributes. To elucidate the intrinsic molecular mechanisms and identify potential biomarkers associated with meat quality, the methodologies employed have evolved from traditional physicochemical parameters (such as color, tenderness, water holding capacity, flavor, and pH) to some cutting-edge omics technologies, including transcriptomics, proteomics, and metabolomics approaches. This review provides a comprehensive analysis of multi-omics techniques and their applications in unraveling sheep and goat meat quality attributes. In addition, the challenges and future perspectives associated with implementing multi-omics technologies in this area of study are discussed. Multi-omics tools can contribute to deciphering the molecular mechanism responsible for the altered the meat quality of sheep and goats across transcriptomic, proteomic, and metabolomic dimensions. The application of multi-omics technologies holds great potential in exploring and identifying biomarkers for meat quality and quality control, thereby promoting the optimization of production processes in the sheep and goat meat industry.

Overlapping genes in natural and engineered genomes

Modern genome-scale methods that identify new genes, such as proteogenomics and ribosome profiling, have revealed, to the surprise of many, that overlap in genes, open reading frames and even coding sequences is widespread and functionally integrated into prokaryotic, eukaryotic and viral genomes. In parallel, the constraints that overlapping regions place on genome sequences and their evolution can be harnessed in bioengineering to build more robust synthetic strains and constructs. With a focus on overlapping protein-coding and RNA-coding genes, this Review examines their discovery, topology and biogenesis in the context of their genome biology. We highlight exciting new uses for sequence overlap to control translation, compress synthetic genetic constructs, and protect against mutation.

A Differential Metabarcoding Approach to Describe Taxonomy Profiles of Bacteria and Archaea in the Saltern of Margherita di Savoia (Italy)

Microorganisms inhabiting saline environments are an interesting ecological model for the study of the adaptation of organisms to extreme living conditions and constitute a precious resource of enzymes and bioproducts for biotechnological applications. We analyzed the microbial communities in nine ponds with increasing salt concentrations (salinity range 4.9–36.0%) of the Saltern of Margherita di Savoia (Italy), the largest thalassohaline saltern in Europe. A deep-metabarcoding NGS procedure addressing separately the V5-V6 and V3-V4 hypervariable regions of the 16S rRNA gene of Bacteria and Archaea, respectively, and a CARD-FISH (catalyzed reporter deposition fluorescence in situ hybridization) analysis allowed us to profile the dynamics of microbial populations at the different salt concentrations. Both the domains were detected throughout the saltern, even if the low relative abundance of Archaea in the three ponds with the lowest salinities prevented the construction of the relative amplicon libraries. The highest cell counts were recorded at 14.5% salinity for Bacteria and at 24.1% salinity for Archaea. While Bacteria showed the greatest number of genera in the first ponds (salinity range 4.9–14.5%), archaeal genera were more numerous in the last ponds of the saltern (salinity 24.1–36.0%). Among prokaryotes, Salinibacter was the genus with the maximum abundance (~49% at 34.6% salinity). Other genera detected at high abundance were the archaeal Haloquadratum (~43% at 36.0% salinity) and Natronomonas (~18% at 13.1% salinity) and the bacterial “Candidatus Aquiluna” (~19% at 14.5% salinity). Interestingly, “Candidatus Aquiluna” had not been identified before in thalassohaline waters.

Comparative Analysis of Strategies for De Novo Transcriptome Assembly in Prokaryotes: Streptomyces clavuligerus as a Case Study

The performance of software tools for de novo transcriptome assembly greatly depends on the selection of software parameters. Up to now, the development of de novo transcriptome assembly for prokaryotes has not been as remarkable as that for eukaryotes. In this contribution, Rockhopper2 was used to perform a comparative transcriptome analysis of Streptomyces clavuligerus exposed to diverse environmental conditions. The study focused on assessing the incidence of software parameters on software performance for the identification of differentially expressed genes as a final goal. For this, a statistical optimization was performed using the Transrate Assembly Score (TAS). TAS was also used for evaluating the software performance and for comparing it with related tools, e.g., Trinity. Transcriptome redundancy and completeness were also considered for this analysis. Rockhopper2 and Trinity reached a TAS value of 0.55092 and 0.58337, respectively. Trinity assembles transcriptomes with high redundancy, with 55.6% of transcripts having some duplicates. Additionally, we observed that the total number of differentially expressed genes (DEG) and their annotation greatly depends on the method used for removing redundancy and the tools used for transcript quantification. To our knowledge, this is the first work aimed at assessing de novo assembly software for prokaryotic organisms.

The Transcriptional landscape of Streptococcus pneumoniae TIGR4 reveals a complex operon architecture and abundant riboregulation critical for growth and virulence

Efficient and highly organized regulation of transcription is fundamental to an organism’s ability to survive, proliferate, and quickly respond to its environment. Therefore, precise mapping of transcriptional units and understanding their regulation is crucial to determining how pathogenic bacteria cause disease and how they may be inhibited. In this study, we map the transcriptional landscape of the bacterial pathogen Streptococcus pneumoniae TIGR4 by applying a combination of high-throughput RNA-sequencing techniques. We successfully map 1864 high confidence transcription termination sites (TTSs), 790 high confidence transcription start sites (TSSs) (742 primary, and 48 secondary), and 1360 low confidence TSSs (74 secondary and 1286 primary) to yield a total of 2150 TSSs. Furthermore, our study reveals a complex transcriptome wherein environment-respondent alternate transcriptional units are observed within operons stemming from internal TSSs and TTSs. Additionally, we identify many putative cis-regulatory RNA elements and riboswitches within 5’-untranslated regions (5’-UTR). By integrating TSSs and TTSs with independently collected RNA-Seq datasets from a variety of conditions, we establish the response of these regulators to changes in growth conditions and validate several of them. Furthermore, to demonstrate the importance of ribo-regulation by 5’-UTR elements for in vivo virulence, we show that the pyrR regulatory element is essential for survival, successful colonization and infection in mice suggesting that such RNA elements are potential drug targets. Importantly, we show that our approach of combining high-throughput sequencing with in vivo experiments can reconstruct a global understanding of regulation, but also pave the way for discovery of compounds that target (ribo-)regulators to mitigate virulence and antibiotic resistance.

The canonical relationship between a bacterial operon and the mRNA transcript produced from the operon has become significantly more complex as numerous regulatory mechanisms that impact the stability, translational efficiency, and early termination rates for mRNA transcripts have been described. With the rise of antibiotic resistance, these mechanisms offer new potential targets for antibiotic development. In this study we used a combination of high-throughput sequencing technologies to assess genome-wide transcription start and stop sites, as well as determine condition specific global transcription patterns in the human pathogen Streptococcus pneumoniae. We find that the majority of multi-gene operons have alternative start and stop sites enabling condition specific regulation of genes within the same operon. Furthermore, we identified many putative RNA regulators that are widespread in the S. pneumoniae pan-genome. Finally, we show that separately collected RNA-Seq data enables identification of conditional triggers for regulatory RNAs, and experimentally demonstrate that our approach may be used to identify drug-able RNA targets by establishing that pyrR RNA functionality is critical for successful S. pneumoniae mouse colonization and infection. Thus, our study not only uses genome-wide high-throughput approaches to identify putative RNA regulators, but also establishes the importance of such regulators in S. pneumoniae virulence.

Antisense transcription in Pseudomonas aeruginosa

A large number of antisense transcripts have been detected in diverse microbial genomes and considerable effort has been devoted to elucidating the functional role of antisense transcription. In this study, we reanalysed extensive RNA sequencing data from the opportunistic pathogen Pseudomonas aeruginosa and found that the majority of genes have a propensity for antisense transcription. Although antisense transcripts were found in more than 80 % of the genes of the P. aeruginosa genome, the majority of sequencing reads were mapping sense and only a minority (<2 %) were mapping antisense to genes. Similarly to the sense expression levels, the antisense expression levels varied under different environmental conditions, with the sense and antisense expression levels often being inversely regulated and modulated by the activity of alternative sigma factors. Environment-modulated antisense transcription showed a bias towards being antisense to genes within regions of genomic plasticity and to those encoding small regulatory RNAs. In the future, the validation and functional characterization of antisense transcripts, and novel transcripts that are antisense to small regulatory RNAs in particular, have the potential to contribute to our understanding of the various levels of transcriptional regulation and its dynamics in the bacterial pathogen P. aeruginosa.