Protein interactome mapping in Caenorhabditis elegans

Intrinsic structural disorder on proteins is involved in the interactome evolution

New mathematical tools help understand cell functions, adaptability, and evolvability to discover hidden variables to predict phenotypes that could be tested in the future in wet labs. Different models have been successfully used to discover the properties of the protein-protein interaction networks or interactomes. I found that in the hyperbolic Popularity-Similarity model, cellular proteins with the highest contents of structural intrinsic disorder cluster together in many different eukaryotic interactomes and this is not the case for the prokaryotic E. coli, where proteins with high degree of intrinsic disorder are scarce. I also found that the normalized theta variable from the Popularity-Similarity model for orthologues proteins correlate to the complexity of the organisms in analysis.

An updated C. elegans nuclear body muscle transcriptome for studies in muscle formation and function

The body muscle is an important tissue used in organisms for proper viability and locomotion. Although this tissue is generally well studied and characterized, and many pathways have been elucidated throughout the years, we still lack a comprehensive understanding of its transcriptome and how it controls muscle development and function. Here, we have updated a nuclear FACS sorting-based methodology to isolate and sequence a high-quality muscle transcriptome from Caenorhabditis elegans mixed-stage animals. We have identified 2848 muscle-specific protein-coding genes, including 78 transcription factors and 206 protein-coding genes containing an RNA binding domain. We studied their interaction network, performed a detailed promoter analysis, and identified novel muscle-specific cis-acting elements. We have also identified 16 high-quality muscle-specific miRNAs, studied their function in vivo using fluorochrome-based analyses, and developed a high-quality C. elegans miRNA interactome incorporating other muscle-specific datasets produced by our lab and others.Our study expands our understanding of how muscle tissue functions in C. elegans andin turn provides results that can in the future be applied to humans to study muscular-related diseases.

Data Incompleteness May form a Hard-to-Overcome Barrier to Decoding Life's Mechanism

In this brief review, we attempt to demonstrate that the incompleteness of data, as well as the intrinsic heterogeneity of biological systems, may form very strong and possibly insurmountable barriers for researchers trying to decipher the mechanisms of the functioning of live systems. We illustrate this challenge using the two most studied organisms: E. coli, with 34.6% genes lacking experimental evidence of function, and C. elegans, with identified proteins for approximately 50% of its genes. Another striking example is an artificial unicellular entity named JCVI-syn3.0, with a minimal set of genes. A total of 31.5% of the genes of JCVI-syn3.0 cannot be ascribed a specific biological function. The human interactome mapping project identified only 5-10% of all protein interactions in humans. In addition, most of the available data are static snapshots, and it is barely possible to generate realistic models of the dynamic processes within cells. Moreover, the existing interactomes reflect the de facto interaction but not its functional result, which is an unpredictable emerging property. Perhaps the completeness of molecular data on any living organism is beyond our reach and represents an unsolvable problem in biology.

A signalling cascade for Ral

Ras is the most mutated oncoprotein in cancer. Among the three oncogenic effectors of Ras - Raf, PI3 Kinase and RalGEF>Ral - signalling through RalGEF>Ral (Ras-like) is by far the least well understood. A variety of signals and binding partners have been defined for Ral, yet we know little of how Ral functions in vivo. This review focuses on previous research in Drosophila that defined a function for Ral in apoptosis and established indirect relationships among Ral, the CNH-domain MAP4 Kinase misshapen, and the JNK MAP kinase basket. Most of the described signalling components are not essential in C. elegans, facilitating subsequent analysis using developmental patterning of the C. elegans vulval precursor cells (VPCs). The functions of two paralogous CNH-domain MAP4 Kinases were defined relative to Ras>Raf, Notch and Ras>RalGEF>Ral signalling in VPCs. MIG-15, the nematode ortholog of misshapen, antagonizes both the Ral-dependent and Ras>Raf-dependent developmental outcomes. In contrast, paralogous GCK-2, the C. elegans ortholog of Drosophila happyhour, propagates the 2°-promoting signal of Ral. Manipulations via CRISPR of Ral signalling through GCK-2 coupled with genetic epistasis delineated a Ras>RalGEF>Ral>Exo84>GCK-2>MAP3K^MLK-1> p38^PMK-1 cascade. Thus, genetic analysis using invertebrate experimental organisms defined a cascade from Ras to p38 MAP kinase.

Worms eat oil: Alcanivorax borkumensis hydrocarbonoclastic bacteria colonise Caenorhabditis elegans nematodes intestines as a first step towards oil spills zooremediation

The environmental hazards of oil spills cannot be underestimated. Bioremediation holds promise among various approaches to tackle oil spills in soils and sediments. In particular, using oil-degrading bacteria is an efficient and self-regulating way to remove oil spills. Using animals for oil spills remediation is in its infancy, mostly due to the lack of efficient oil-degrading capabilities in eukaryotes. Here we show that Caenorhabditis elegans nematodes survive for extended periods (up to 22 days) on pure crude oil diet. Moreover, we report for the first time the use of Alcanivorax borkumensis hydrocarbonoclastic bacteria for colonisation of C. elegans intestines, which allows for effective digestion of crude oil by the nematodes. The worms fed and colonised by A. borkumensis demonstrated the similar or even better longevity, resistance against oxidative and thermal stress and reproductivity as those animals fed with Escherichia coli bacteria (normal food). Importantly, A. borkumensis-carrying nematodes were able to accumulate oil droplet from oil-contaminated soils. Artificial colonisation of soil invertebrates with oil-degrading bacteria will be an efficient way to distribute microorganisms in polluted soil, thus opening new avenues for oil spills zooremediation.

Identification of AIDS-Associated Kaposi Sarcoma: A Functional Genomics Approach

BACKGROUND

Kaposi sarcoma-associated herpes virus (KSHV) is one of the most common causal agents of Kaposi Sarcoma (KS) in individuals with HIV-infections. The virus has gained attention over the past few decades due to its remarkable pathogenic mechanisms. A group of genes, ORF71, ORF72, and ORF73, are expressed as polycistronic mRNAs and the functions of ORF71 and ORF72 in KSHV are already reported in the literature. However, the function of ORF73 has remained a mystery. The aim of this study is to conduct comprehensive exploratory experiments to clarify the role of ORF73 in KSHV pathology and discover markers of AIDS-associated KSHV-induced KS by bioinformatic approaches.

METHODS AND RESULTS

We searched for homologues of ORF-73 and attempted to predict protein-protein interactions (PPI) based on GeneCards and UniProtKB, utilizing Position-Specific Iterated BLAST (PSI-BLAST). We applied Gene Ontology (GO) and KEGG pathway analyses to identify highly conserved regions between ORF-73 and p53to help us identify potential markers with predominant hits and interactions in the KEGG pathway associated with host apoptosis and cell arrest. The protein p53 is selected because it is an important tumor suppressor antigen. To identify the potential roles of the candidate markers at the molecular level, we used PSIPRED keeping the conserved domains as the major parameters to predict secondary structures. We based the FUGE interpretation consolidations of the sequence-structure comparisons on distance homology, where the score for the amino acids matching the insertion/deletion (indels) detected were based on structures compared to the FUGE database of structural profiles. We also calculated the compatibility scores of sequence alignments accordingly. Based on the PSI-BLAST homologues, we checked the disordered structures predicted using PSI-Pred and DISO-Pred for developing a hidden Markov model (HMM). We further applied these HMMs models based on the alignment of constructed 3D models between the known structure and the HMM of our sequence. Moreover, stable homology and structurally conserved domains confirmed that ORF-73 maybe an important prognostic marker for AIDS-associated KS.

CONCLUSION

Collectively, similar variants of ORF-73 markers involved in the immune response may interact with targeted host proteins as predicted by our computational analysis. This work also suggests the existence of potential conformational changes that need to be further explored to help elucidate the role of immune signaling during KS towards the development of therapeutic applications.