Unraveling the complex relationship between mRNA and protein abundances: a machine learning-based approach for imputing protein levels from RNA-seq data.

The correlation between messenger RNA (mRNA) and protein abundances has long been debated. RNA sequencing (RNA-seq), a high-throughput, commonly used method for analyzing transcriptional dynamics, leaves questions about whether we can translate RNA-seq-identified gene signatures directly to protein changes. In this study, we utilized a set of 17 widely assessed immune and wound healing mediators in the context of canine volumetric muscle loss to investigate the correlation of mRNA and protein abundances. Our data reveal an overall agreement between mRNA and protein levels on these 17 mediators when examining samples from the same experimental condition (e.g. the same biopsy). However, we observed a lack of correlation between mRNA and protein levels for individual genes under different conditions, underscoring the challenges in converting transcriptional changes into protein changes. To address this discrepancy, we developed a machine learning model to predict protein abundances from RNA-seq data, achieving high accuracy. Our approach also effectively corrected multiple extreme outliers measured by antibody-based protein assays. Additionally, this model has the potential to detect post-translational modification events, as shown by accurately estimating activated transforming growth factor ß1 levels. This study presents a promising approach for converting RNA-seq data into protein abundance and its biological significance.

Immune system roles in pathogenesis, prognosis, control, and treatment of Toxoplasma gondii infection.

Toxoplasma gondii is the protozoan causative agent of toxoplasmosis in humans and warm-blooded animals. Recent studies have illustrated that the immune system plays a pivotal role in the pathogenesis of toxoplasmosis by triggering immune cytokines like IL-12, TNF-α, and IFN-γ and immune cells like DCs, Th1, and Th17. On the other hand, some immune components can serve as prognosis markers of toxoplasmosis. In healthy people, the disease is often asymptomatic, but immunocompromised people and newborns may suffer severe symptoms and complications. Therefore, the immune prognostic markers may provide tools to measure the disease progress and help patients to avoid further complications. Immunotherapies using monoclonal antibody, cytokines, immune cells, exosomes, novel vaccines, and anti-inflammatory molecules open new horizon for toxoplasmosis treatment. In this review article, we discussed the immunopathogenesis, prognosis, and immunotherapy of Toxoplasma gondii infection.

A Nile rat transcriptomic landscape across 22 organs by ultra-deep sequencing and comparative RNA-seq pipeline (CRSP).

RNA sequencing (RNA-seq) has been a widely used high-throughput method to characterize transcriptomic dynamics spatiotemporally. However, RNA-seq data analysis pipelines typically depend on either a sequenced genome and/or corresponding reference transcripts. This limitation is a challenge for species lacking sequenced genomes and corresponding reference transcripts. The Nile rat (Arvicanthis niloticus) has two key features - it is daytime active, and it is prone to diet-induced diabetes, which makes it more similar to humans than regular laboratory rodents. However, at the time of this study, neither a Nile rat genome nor a reference transcript set were available, making it technically challenging to perform large-scale RNA-seq based transcriptomic studies. This genome-independent work progressed concurrently with our generation of a Nile rat genome. A well-annotated genome requires several iterations of manually reviewing curated transcripts and takes years to achieve. Here, we developed a Comparative RNA-Seq Pipeline (CRSP), integrating a comparative species strategy independent of a specific sequenced genome or species-matched reference transcripts. We performed benchmarking to validate that our CRSP tool can accurately quantify gene expression levels. In this study, we generated the first ultra-deep (2.3 billion × 2 paired-end) Nile rat RNA-seq data from 59 biopsy samples representing 22 major organs, providing a unique resource and spatial gene expression reference for Nile rat researchers. Importantly, CRSP is not limited to the Nile rat species and can be applied to any species without prior genomic knowledge. To facilitate a general use of CRSP, we also characterized the number of RNA-seq reads required for accurate estimation via simulation studies. CRSP and documents are available at: https://github.com/pjiang1105/CRSP.

Tracing Translational Footprint by Ribo-Seq: Principle, Workflow, and Applications to Understand the Mechanism of Human Diseases.

RNA-seq has been widely used as a high-throughput method to characterize transcript dynamic changes in a broad context, such as development and diseases. However, whether RNA-seq-estimated transcriptional dynamics can be translated into protein level changes is largely unknown. Ribo-seq (Ribosome profiling) is an emerging technology that allows for the investigation of the translational footprint via profiling ribosome-bounded mRNA fragments. Ribo-seq coupled with RNA-seq will allow us to understand the transcriptional and translational control of the fundamental biological process and human diseases. This review focuses on discussing the principle, workflow, and applications of Ribo-seq to study human diseases.

Remote Ischemic Perconditioning Modulates Apelin Expression After Renal Ischemia-Reperfusion Injury.

BACKGROUND: Renal ischemia/reperfusion injury (IRI) can result in impaired ability of urine concentration and increased sodium fractional excretion. Apelin, a (neuro) vasoactive peptide, enhances diuresis by increasing the renal microcirculation and by counteracting the antidiuretic effect of arginine vasopressin on the tubules. However, changes in renal apelin expression in renal IRI rat model have not been elucidated. Remote ischemic perconditioning (RIPerC) improves renal sodium and water handling after IRI. Here, we investigated whether RIPerC prevents dysregulation of renal sodium and water handling in response to IRI by apelin signaling pathway in rats. MATERIALS AND METHODS: Renal IRI was induced by 45-min clamping of renal arteries followed by 24 h reperfusion. RIPerC was created by applying four cycles of 2-min ischemia of the left femoral artery followed by 3-min reperfusion at the start of renal ischemia. Rats were randomly divided into sham, ischemia/reperfusion, and RIPerC + ischemia/reperfusion groups. Urine and blood were sampled after reperfusion period. The kidney was harvested for mRNA isolation and histopathological study. RESULTS: IRI resulted in decreased clearance of creatinine, increased sodium fractional excretion, and reduced urine osmolality compared with sham animals. This occurred with an increase in mRNA expression levels of apelin and histological damages in both cortical and medullary regions of kidney tissues. RIPerC treatment ameliorated all these changes. CONCLUSIONS: This study showed that RIPerC has protective effects against dysregulation of renal sodium and water handling after renal IRI, which might be related with inhibition of apelin signaling pathway.