Paniz Jasbi

The field of multi-omics has witnessed unprecedented growth, converging multiple scientific disciplines and technological advances. This surge is evidenced by a more than doubling in multi-omics scientific publications within just two years (2022–2023) since its first referenced mention in 2002, as indexed by the National Library of Medicine. This emerging field has demonstrated its capability to provide comprehensive insights into complex biological systems, representing a transformative force in health diagnostics and therapeutic strategies. However, several challenges are evident when merging varied omics data sets and methodologies, interpreting vast data dimensions, streamlining longitudinal sampling and analysis, and addressing the ethical implications of managing sensitive health information. This review evaluates these challenges while spotlighting pivotal milestones: the development of targeted sampling methods, the use of artificial intelligence in formulating health indices, the integration of sophisticated n-of-1 statistical models such as digital twins, and the incorporation of blockchain technology for heightened data security. For multi-omics to truly revolutionize healthcare, it demands rigorous validation, tangible real-world applications, and smooth integration into existing healthcare infrastructures. It is imperative to address ethical dilemmas, paving the way for the realization of a future steered by omics-informed personalized medicine.

Systemic inflammation is associated with chronic disease and is purported to be a main pathogenic mechanism underlying metabolic conditions. Microbes harbored in the host gastrointestinal tract release signaling byproducts from their cell wall, such as lipopolysaccharides (LPS), which can act locally and, after crossing the gut barrier and entering circulation, also systemically. Defined as metabolic endotoxemia, elevated concentrations of LPS in circulation are associated with metabolic conditions and chronic disease. As such, measurement of LPS is highly prevalent in animal and human research investigating these states. Indeed, LPS can be a potent stimulant of host immunity, but this response depends on the microbial species' origin, a parameter often overlooked in both preclinical and clinical investigations. Indeed, the lipid A portion of LPS is mutable and comprises the main virulence and endotoxic component, thus contributing to the structural and functional diversity among LPSs from microbial species. In this review, we discuss how such structural differences in LPS can induce differential immunological responses in the host.

Breast cancer (BC) is a common cause of morbidity and mortality, particularly in women. Moreover, the discovery of diagnostic biomarkers for early BC remains a challenging task. Previously, we [Jasbi et al. J. Chromatogr. B. 2019, 1105, 26−37] demonstrated a targeted metabolic profiling approach capable of identifying metabolite marker candidates that could enable highly sensitive and specific detection of BC. However, the coverage of this targeted method was limited and exhibited suboptimal classification of early BC (EBC). To expand the metabolome coverage and articulate a better panel of metabolites or mass spectral features for classification of EBC, we evaluated untargeted liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QTOF-MS) data, both individually as well as in conjunction with previously published targeted LC-triple quadruple (QQQ)-MS data. Variable importance in projection scores were used to refine the biomarker panel, whereas orthogonal partial least squares-discriminant analysis was used to operationalize the enhanced biomarker panel for early diagnosis. In this approach, 33 altered metabolites/features were detected by LC-QTOF-MS from 124 BC patients and 86 healthy controls. For EBC diagnosis, significance testing and analysis of the area under receiver operating characteristic (AUROC) curve identified six metabolites/features [ethyl (R)-3-hydroxyhexanoate; caprylic acid; hypoxanthine; and m/z 358.0018, 354.0053, and 356.0037] with p < 0.05 and AUROC > 0.7. These metabolites informed the construction of EBC diagnostic models; evaluation of model performance for the prediction of EBC showed an AUROC = 0.938 (95% CI: 0.895–0.975), with sensitivity = 0.90 when specificity = 0.90. Using the combined untargeted and targeted data set, eight metabolic pathways of potential biological relevance were indicated to be significantly altered as a result of EBC. Metabolic pathway analysis showed fatty acid and aminoacyl-tRNA biosynthesis as well as inositol phosphate metabolism to be most impacted in response to the disease. The combination of untargeted and targeted metabolomics platforms has provided a highly predictive and accurate method for BC and EBC diagnosis from plasma samples. Furthermore, such a complementary approach yielded critical information regarding potential pathogenic mechanisms underlying EBC that, although critical to improved prognosis and enhanced survival, are understudied in the current literature. All mass spectrometry data and deidentified subject metadata analyzed in this study have been deposited to Mendeley Data and are publicly available (DOI: 10.17632/kcjg8ybk45.1).

ABSTRACT Antibiotic-induced alterations in the gut ecosystem increases the susceptibility to Candida albicans, yet the mechanisms involved remains poorly understood. Here we show that mice treated with the broad-spectrum antibiotic cefoperazone promoted the growth, morphogenesis and gastrointestinal (GI) colonization of C. albicans. Using metabolomics, we revealed that the cecal metabolic environment of the mice treated with cefoperazone showed a significant alteration in intestinal metabolites. Levels of carbohydrates, sugar alcohols and primary bile acids increased, whereas carboxylic acids and secondary bile acids decreased in antibiotic treated mice susceptible to C. albicans. Furthermore, using in-vitro assays, we confirmed that carbohydrates, sugar alcohols and primary bile acids promote, whereas carboxylic acids and secondary bile acids inhibit the growth and morphogenesis of C. albicans. In addition, in this study we report changes in the levels of gut metabolites correlated with shifts in the gut microbiota. Taken together, our in-vivo and in-vitro results indicate that cefoperazone-induced metabolome and microbiome alterations favor the growth and morphogenesis of C. albicans, and potentially play an important role in the GI colonization of C. albicans.