Omics A Journal of Integrative Biology最新文献

Cancer research calls for new approaches that account for the regulatory complexities of biology. We present, in this study, the differential transcriptional regulome (DIFFREG) approach for the identification and prioritization of key transcriptional regulators and apply it to the case of renal cell carcinoma (RCC) biology. Of note, RCC has a poor prognosis and the biomarker and drug discovery studies to date have tended to focus on gene expression independent from mutations and/or post-translational modifications. DIFFREG focuses on the differential regulation between transcription factors (TFs) and their target genes rather than differential gene expression and integrates transcriptome profiling with the human transcriptional regulatory network to analyze differential gene regulation between healthy and RCC cases. In this study, RNA-seq tissue samples (n = 1020) from the Cancer Genome Atlas (TCGA), including healthy and tumor subjects, were integrated with a comprehensive human TF-gene interactome dataset (1122603 interactions between 1289 TFs and 25177 genes). Comparative analysis of DIFFREG profiles, consisting of perturbed TF-gene interactions, from three common subtypes (clear cell RCC, papillary RCC and chromophobe RCC) revealed subtype-specific alterations, supporting the hypothesis that these signatures in the transcriptional regulome profiles may be considered potential biomarkers that may play an important role in elucidating the molecular mechanisms of RCC development and translating knowledge about the genetic basis of RCC into the clinic. In addition, these indicators may help oncologists make the best decisions for diagnosis and prognosis management.

Data quality is often an overlooked feature in the analysis of omics data. This is particularly relevant in studies of chemical and pathogen exposures that can modify an individual's epigenome and transcriptome with persistence over time. Portable, quality control (QC) pipelines for multiple different omics datasets are therefore needed. To meet these goals, portable quality assurance (QA) metrics, metric acceptability criterion, and pipelines to compute these metrics were developed and consolidated into one framework for 12 different omics assays. Performance of these QA metrics and pipelines were evaluated on human data generated by the Defense Advanced Research Projects Agency (DARPA) Epigenetic CHaracterization and Observation (ECHO) program. Twelve analytical pipelines were developed leveraging standard tools when possible. These QC pipelines were containerized using Singularity to ensure portability and scalability. Datasets for these 12 omics assays were analyzed and results were summarized. The quality thresholds and metrics used were described. We found that these pipelines enabled early identification of lower quality datasets, datasets with insufficient reads for additional sequencing, and experimental protocols needing refinements. These omics data analysis and QC pipelines are available as open-source resources as reported and discussed in this article for the omics and life sciences communities.

Critically informed engagement in politics and the knowledge of social theory help democratize knowledge production, and redress power asymmetries in science and society. A feminist lens is one of the many ways in which power asymmetries in science can be critically unpacked and interrupted. There are many strands of feminism and feminist theory that differ in their approaches to resist patriarchy and injustices in science and society. As an example, I adopt here the definition of feminism of the late cultural critic bell hooks because her works underscore that feminism is an intersectional liberatory methodology for everyone to resist multiple forms of oppression simultaneously. Queer theory is a strand of social theory that came to prominence since the 1990s in particular. Queer feminism continues to shape feminist writing on science cultures and the knowledge-based innovations contemporary science strives to accomplish. Systems science brings about systems thinking, and that includes rethinking science as culture beyond a narrow realm of technology, and being cognizant of the broader social, feminist, queer, and political contexts of science around the world.

Advances in digital health, systems biology, environmental monitoring, and artificial intelligence (AI) continue to revolutionize health care, ushering a precision health future. More than disease treatment and prevention, precision health aims at maintaining good health throughout the lifespan. However, how can precision health impact care for people with a terminal or life-limiting condition? We examine here the ethical, equity, and societal/relational implications of two precision health modalities, (1) integrated systems biology/multi-omics analysis for disease prognostication and (2) digital health technologies for health status monitoring and communication. We focus on three main ethical and societal considerations: benefits and risks associated with integration of these modalities into the palliative care system; inclusion of underrepresented and marginalized groups in technology development and deployment; and the impact of high-tech modalities on palliative care's highly personalized and "high-touch" practice. We conclude with 10 recommendations for ensuring that precision health technologies, such as multi-omics prognostication and digital health monitoring, for palliative care are developed, tested, and implemented ethically, inclusively, and equitably.

The use of high-throughput sequencing technologies and bioinformatic tools has greatly transformed microbial genome research. With the help of sophisticated computational tools, it has become easier to perform whole genome assembly, identify and compare different species based on their genomes, and predict the presence of genes responsible for proteins, antimicrobial resistance, and toxins. These bioinformatics resources are likely to continuously improve in quality, become more user-friendly to analyze the multiple genomic data, efficient in generating information and translating it into meaningful knowledge, and enhance our understanding of the genetic mechanism of AMR. In this manuscript, we provide an essential guide for selecting the popular resources for microbial research, such as genome assembly and annotation, antibiotic resistance gene profiling, identification of virulence factors, and drug interaction studies. In addition, we discuss the best practices in computer-oriented microbial genome research, emerging trends in microbial genomic data analysis, integration of multi-omics data, the appropriate use of machine-learning algorithms, and open-source bioinformatics resources for genome data analytics.

Pharmacists play a pivotal role in pharmacogenomic (PGx) implementation in clinical practice, and their university education is considered a strong driver in holding favorable intentions toward PGx adoption. Using a survey developed based on the Theory of Planned Behavior (TPB), this study aimed to evaluate the determinants of senior pharmacy students' intentions to pursue postgraduate training in PGx and personalized medicine (PM), and with an eye to propose interventions to inform pharmacy students' career choices in the field. Students manifested considerably favorable attitudes toward PGx clinical practice and had acquired a relatively satisfactory level of knowledge. However, they conceded of having a hardly moderate level of confidence in PGx clinical application, and claimed to be moderately satisfied with their PGx training. Interestingly, students alleged to have a relatively limited interest to pursue postgraduate training studies in PGx and PM. Gender was a key and significant demographic moderator of the students' intentions to pursue postgraduate training in PGx and PM. We found that the students' attitudes exerted a strong positive impact on intentions for future PGx training, while self-confidence and training satisfaction had a moderate positive effect, respectively. We propose a set of key interventions that include, inter alia, the update of existing pharmacy curricula and the promotion of interdisciplinary collaborations with other health professionals, to reinforce the pharmacists' role in PM and PGx implementation in clinical practice. To the best of our knowledge, this is the first study using the TPB to identify the role of certain factors such as gender, attitudes, self-confidence, and training satisfaction on the final-year pharmacy undergraduate students' intentions to pursue PGx-related postgraduate studies in the future.

Chronic inflammation is an important contributor to tumorigenesis in many tissues. However, the underlying mechanisms of inflammatory signaling in the tumor microenvironment are not yet fully understood in various cancers. Therefore, this study aimed to uncover the gene expression signatures of inflammation-associated proteins that lead to tumorigenesis, and with an eye to discovery of potential system biomarkers and novel drug candidates in oncology. Gene expression profiles associated with 12 common cancers (e.g., breast invasive carcinoma, colon adenocarcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma) from The Cancer Genome Atlas were retrieved and mapped to inflammation-related gene sets. Subsequently, the inflammation-associated differentially expressed genes (i-DEGs) were determined. The i-DEGs common in all cancers were proposed as tumor inflammation signatures (TIS) after pan-cancer analysis. A TIS, consisting of 45 proteins, was evaluated as a potential system biomarker based on its prognostic forecasting and secretion profiles in multiple tissues. In addition, i-DEGs for each cancer type were used as queries for drug repurposing. Narciclasine, parthenolide, and homoharringtonine were identified as potential candidates for drug repurposing. Biomarker candidates in relation to inflammation were identified such as KNG1, SPP1, and MIF. Collectively, these findings inform precision diagnostics development to distinguish individual cancer types, and can also pave the way for novel prognostic decision tools and repurposed drugs across multiple cancers. These new findings and hypotheses warrant further research toward precision/personalized medicine in oncology. Pan-cancer analysis of inflammatory mediators can open up new avenues for innovation in cancer diagnostics and therapeutics.

Systems biology tools offer new prospects for industrial strain selection. For bacteria that are significant for industrial applications, whole-genome sequencing coupled to flux balance analysis (FBA) can help unpack the complex relationships between genome mutations and carbon trafficking. This work investigates the l-tyrosine (l-Tyr) overproducing model system Corynebacterium glutamicum ATCC 21573 with an eye to more rational and precision strain development. Using genome-wide mutational analysis of C. glutamicum, we identified 27,611 single nucleotide polymorphisms and 479 insertion/deletion mutations. Mutations in the carbon uptake machinery have led to phosphotransferase system-independent routes as corroborated with FBA. Mutations within the central carbon metabolism of C. glutamicum impaired the carbon flux, as evidenced by the lower growth rate. The entry to and flow through the tricarboxylic acid cycle was affected by mutations in pyruvate and α-ketoglutarate dehydrogenase complexes, citrate synthase, and isocitrate dehydrogenase. FBA indicated that the estimated flux through the shikimate pathway became larger as the l-Tyr production rate increased. In addition, protocatechuate export was probabilistically impossible, which could have contributed to the l-Tyr accumulation. Interestingly, aroG and cg0975, which have received previous attention for aromatic amino acid overproduction, were not mutated. From the branch point molecule, prephenate, the change in the promoter region of pheA could be an influential contributor. In summary, we suggest that genome sequencing coupled with FBA is well poised to offer rational guidance for industrial strain development, as evidenced by these findings on carbon trafficking in C. glutamicum ATCC 21573.