Gene Expression Analysis Through Network Biology: Bioinformatics Approaches

Molecular Signatures for Microbe-Associated Colorectal Cancers

Background

Genetic factors and microbial imbalances play crucial roles in colorectal cancers (CRCs), yet the impact of infections on cancer initiation remains poorly understood. While bioinformatic approaches offer valuable insights, the rising incidence of CRCs creates a pressing need to precisely identify early CRC events. We constructed a network model to identify continuum states during CRC initiation spanning normal colonic tissue to pre-cancer lesions (adenomatous polyps) and examined the influence of microbes and host genetics.

Methods

A Boolean network was built using a publicly available transcriptomic dataset from healthy and adenoma affected patients to identify an invariant Microbe-Associated Colorectal Cancer Signature (MACS). We focused on Fusobacterium nucleatum ( Fn ), a CRC-associated microbe, as a model bacterium. MACS-associated genes and proteins were validated by RT-qPCR, RNA seq, ELISA, IF and IHCs in tissues and colon-derived organoids from genetically predisposed mice ( CPC-APC Min+/- ) and patients (FAP, Lynch Syndrome, PJS, and JPS).

Results

The MACS that is upregulated in adenomas consists of four core genes/proteins: CLDN2/Claudin-2 (leakiness), LGR5/leucine-rich repeat-containing receptor (stemness), CEMIP/cell migration-inducing and hyaluronan-binding protein (epithelial-mesenchymal transition) and IL8/Interleukin-8 (inflammation). MACS was induced upon Fn infection, but not in response to infection with other enteric bacteria or probiotics. MACS induction upon Fn infection was higher in CPC-APC Min+/- organoids compared to WT controls. The degree of MACS expression in the patient-derived organoids (PDOs) generally corresponded with the known lifetime risk of CRCs.

Conclusions

Computational prediction followed by validation in the organoid-based disease model identified the early events in CRC initiation. MACS reveals that the CRC-associated microbes induce a greater risk in the genetically predisposed hosts, suggesting its potential use for risk prediction and targeted cancer prevention.

Global Transcriptional Insights of Pollen-Pistil Interactions Commencing Self-Incompatibility and Fertilization in Tea [Camellia sinensis (L.) O. Kuntze]

This study explicates molecular insights commencing Self-Incompatibility (SI) and CC (cross-compatibility/fertilization) in self (SP) and cross (CP) pollinated pistils of tea. The fluorescence microscopy analysis revealed ceased/deviated pollen tubes in SP, while successful fertilization occurred in CP at 48 HAP. Global transcriptome sequencing of SP and CP pistils generated 109.7 million reads with overall 77.9% mapping rate to draft tea genome. Furthermore, concatenated de novo assembly resulted into 48,163 transcripts. Functional annotations and enrichment analysis (KEGG & GO) resulted into 3793 differentially expressed genes (DEGs). Among these, de novo and reference-based expression analysis identified 195 DEGs involved in pollen-pistil interaction. Interestingly, the presence of 182 genes [PT germination & elongation (67), S-locus (11), fertilization (43), disease resistance protein (30) and abscission (31)] in a major hub of the protein-protein interactome network suggests a complex signaling cascade commencing SI/CC. Furthermore, tissue-specific qRT-PCR analysis affirmed the localized expression of 42 DE putative key candidates in stigma-style and ovary, and suggested that LSI initiated in style and was sustained up to ovary with the active involvement of csRNS, SRKs & SKIPs during SP. Nonetheless, COBL10, RALF, FERONIA-rlk, LLG and MAPKs were possibly facilitating fertilization. The current study comprehensively unravels molecular insights of phase-specific pollen-pistil interaction during SI and fertilization, which can be utilized to enhance breeding efficiency and genetic improvement in tea.