Thrombin-Activatable Fibrinolysis Inhibitor (TAFI) is a carboxypeptidase B-like proenzyme encoded by the CPB2 gene. After thrombin activation, TAFI downregulates fibrinolysis, thus linking the latter with coagulation. TAFI has been shown to play a role in venous and arterial thrombotic diseases, yet, data regarding the molecular mechanisms underlying its function have been conflicting. In this study, we focused on the prediction and functional enrichment analysis (FEA) of the TAFI interaction network and the microRNAs (miRNAs) targeting the members of this network in an attempt to identify novel components and pathways of TAFI-related thrombosis. To this end, we used nine bioinformatics software tools. We found that the TAFI interactome consists of 28 unique genes mainly involved in hemostasis. Twenty-four miRNAs were predicted to target these genes. Co-annotation analysis of the predicted interactors with respect to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and transcription factors (TFs) pointed to the complement and coagulation cascades as well as neutrophil extracellular trap formation. Cancer, stroke, and intracranial aneurysm were among the top 20 significant diseases related to the identified miRNAs. We reason that the predicted biomolecules should be further studied in the context of TAFI-related thrombosis.

Nicotinamide adenine dinucleotide (NAD) levels are essential for the normal physiology of the cell and are strictly regulated to prevent pathological conditions. NAD functions as a coenzyme in redox reactions, as a substrate of regulatory proteins, and as a mediator of protein-protein interactions. The main objectives of this study were to identify the NAD-binding and NAD-interacting proteins, and to uncover novel proteins and functions that could be regulated by this metabolite. It was considered if cancer-associated proteins were potential therapeutic targets. Using multiple experimental databases, we defined datasets of proteins that directly interact with NAD - the NAD-binding proteins (NADBPs) dataset - and of proteins that interact with NADBPs - the NAD-protein-protein interactions (NAD-PPIs) dataset. Pathway enrichment analysis revealed that NADBPs participate in several metabolic pathways, while NAD-PPIs are mostly involved in signalling pathways. These include disease-related pathways, namely, three major neurodegenerative disorders: Alzheimer\'s disease, Huntington\'s disease, and Parkinson\'s disease. Then, the complete human proteome was further analysed to select potential NADBPs. TRPC3 and isoforms of diacylglycerol (DAG) kinases, which are involved in calcium signalling, were identified as new NADBPs. Potential therapeutic targets that interact with NAD were identified, that have regulatory and signalling functions in cancer and neurodegenerative diseases.

Coronavirus disease 2019 (COVID-19) is a pandemic respiratory disease associated with high morbidity and mortality. Although many patients recover, long-term sequelae after infection have become increasingly recognized and concerning. Among other sequelae, the available data indicate that many patients who recover from COVID-19 could develop fibrotic abnormalities over time. To understand the basic pathophysiology underlying the development of long-term pulmonary fibrosis in COVID-19, as well as the higher mortality rates in patients with pre-existing lung diseases, we compared the transcriptomic fingerprints among patients with COVID-19, idiopathic pulmonary fibrosis (IPF), and chronic obstructive pulmonary disease (COPD) using interactomic analysis. Patients who died of COVID-19 shared some of the molecular biological processes triggered in patients with IPF, such as those related to immune response, airway remodeling, and wound healing, which could explain the radiological images seen in some patients after discharge. However, other aspects of this transcriptomic profile did not resemble the profile associated with irreversible fibrotic processes in IPF. Our mathematical approach instead showed that the molecular processes that were altered in COVID-19 patients more closely resembled those observed in COPD. These data indicate that patients with COPD, who have overcome COVID-19, might experience a faster decline in lung function that will undoubtedly affect global health.

To characterize serum microRNA (miR) and the miR interactome of active RA patients in RA aetiology and pathogenesis.
The differentially expressed miRs (DEmiRs) in serum of naïve active RA patients (NARAPs, n = 9, into three pools) vs healthy controls (HCs, n = 15, into five pools) were identified with Agilent human miR microarray analysis. Candidate driver genes in epigenetic and pathogenic signalling pathway modules for RA were analysed using miRTarBase and a molecular complex detection algorithm. The interactome of these DEmiRs in RA pathogenesis were further characterized with gene ontology and Kyoto Encyclopaedia of Genes and Genomes.
Three upregulated DEmiRs (hsa-miR-187-5p, -4532, -4516) and eight downregulated DEmiRs (hsa-miR-125a-3p, -575, -191-3p, -6865-3p, -197-3p, -6886-3p, -1237-3p, -4436b-5p) were identified in NARAPs. Interactomic analysis from heterogeneous experimentally validated sources yielded 1719 miR-target interactions containing 5.67% strong and 94.33% less strong experimental evidence. Gene ontology and Kyoto Encyclopaedia of Genes and Genomes analyses allocated the upregulated DEmiRs in the infection modules and the downregulated DEmiRs in the immune signalling pathways. Specifically, these DEmiRs revealed the significant contributions of the intestinal microbiome dysbiosis in the infection-inflammation-immune network for activation of T cells, immune pathways of IL-17, Toll-like receptor, TNF, Janus kinase-signal transducer and activator of transcription, osteoclast cell differentiation pathway and IgA production to the active RA pathogenesis.
Our experiment-based interactomic study of DEmiRs in serum of NARAPs revealed novel clinically relevant miRs interactomes in the infection-inflammation-immune network of RA. These results provide valuable resources for understanding the integrated function of the miR network in RA pathogenesis and the application of circulating miRs as biomarkers for early aetiologic RA diagnosis.

Background and Objectives: The defects in the CLDN16 gene are a cause of primary hypomagnesemia (FHHNC), which is characterized by massive renal magnesium wasting, resulting in nephrocalcinosis and renal failure. The mutations occur throughout the gene\'s coding region and can impact on intracellular trafficking of the protein or its paracellular pore forming function. To gain more understanding about the mechanisms by which CLDN16 mutations can induce FHHNC, we performed an in-depth computational analysis of the CLDN16 gene and protein, focusing specifically on the prediction of the latter\'s subcellular localization. Materials and Methods: The complete nucleotide or amino acid sequence of CLDN16 in FASTA format was entered and processed in 14 databases. Results: One CpG island was identified. Twenty five promoters/enhancers were predicted. The CLDN16 interactome was found to consist of 20 genes, mainly involved in kidney diseases. No signal peptide cleavage site was identified. A probability of export to mitochondria equal to 0.9740 and a cleavable mitochondrial localization signal in the N terminal of the CLDN16 protein were predicted. The secondary structure prediction was visualized. Νo phosphorylation sites were identified within the CLDN16 protein region by applying DISPHOS to the functional class of transport. The KnotProt database did not predict any knot or slipknot in the protein structure of CLDN16. Seven putative miRNA binding sites within the 3\'-UTR region of CLDN16 were identified. Conclusions: This is the first study to identify mitochondria as a probable cytoplasmic compartment for CLDN16 localization, thus providing new insights into the protein\'s intracellular transport. The results relative to the CLDN16 interactome underline its role in renal pathophysiology and highlight the functional dependence of CLDNs-10, 14, 16, 19. The predictions pertaining to the miRNAs, promoters/enhancers and CpG islands of the CLDN16 gene indicate a strict regulation of its expression both transcriptionally and post-transcriptionally.

For over sixty years, it has been known that mammalian spermatozoa immediately after ejaculation are virtually infertile. They became able to fertilize only after they reside for long time (hours to days) within female genital tract where they complete their functional maturation, the capacitation. This process is finely regulated by the interaction with the female environment and involves, in spermatozoa, a myriad of molecules as messengers and target of signals. Since, to date, a model able to represent the molecular interaction that characterize sperm physiology does not exist, we realized the Human Sperm Interactme Network3.0 (HSIN3.0) and its main component (HSNI3.0_MC), starting from the pathway active in male germ cells.
HSIN3.0 and HSIN3.0_MC are scale free networks, adherent to the Barabasi-Albert model, and are characterised by an ultra-small world topology. We found that they are resistant to random attacks and that are designed to respond quickly and specifically to external inputs. In addition, it has been possible to identify the most connected nodes (the hubs) and the bottlenecks nodes. This result allowed us to explore the control mechanisms active in driving sperm biochemical machinery and to verify the different levels of controls: party vs. date hubs and hubs vs. bottlenecks, thanks the availability of data from KO mice. Finally, we found that several key nodes represent molecules specifically involved in function that are thought to be not present or not active in sperm cells, such as control of cell cycle, proteins synthesis, nuclear trafficking, and immune response, thus potentially open new perspectives on the study of sperm biology.
For the first time we present a network representing putative human sperm interactome. This result gives very intriguing biological information and could contribute to the knowledge of spermatozoa, either in physiological or pathological conditions.

Host-pathogen interaction is one of the most important areas of study to understand the adhesion of the pathogen to the host organisms. To adhere on the host cell surface, bacteria assemble the diverse adhesive structures on its surface, which play a foremost role in targeting to the host cell. We have highlighted different bacterial adhesins which are either protein mediated or glycan mediated. The present article listed examples of different bacterial adhesin proteins involved in the interactions with their host, types and subtypes of the fimbriae and non-fimbriae bacterial adhesins. Different bacterial surface adhesin subunits interact with host via different host surface biomolecules. We have also discussed the interactome of some of the pathogens with their host. Therefore, the present study will help researchers to have a detailed understanding of different interacting bacterial adhesins and henceforth, develop new therapies, adhesin specific antibodies and vaccines, which can effectively control pathogenicity of the pathogens.

Autophagy is an extremely dynamic process that mediates the rapid degradation of intracellular components in response to different stress conditions. The autophagic response is executed by specific protein complexes, whose function is regulated by posttranslational modifications and interactions with positive and negative regulators. A comprehensive analysis of how autophagy complexes are temporally modified upon stress stimuli is therefore particularly relevant to understand how this pathway is regulated. Here, we describe a method to define the protein-protein interaction network of a central complex involved in autophagy induction, the Beclin 1 complex. This method is based on the quantitative comparison of protein complexes immunopurified at different time points using a stable isotope labeling by amino acids in cell culture approach. Understanding how the Beclin 1 complex dynamically changes in response to different stress stimuli may provide useful insights to disclose novel molecular mechanisms responsible for the dysregulation of autophagy in pathological conditions, such as cancer, neurodegeneration, and infections.

Very often dysfunctional aspects of various signalling networks are found to be associated with human diseases and disorders. The major characteristics of signal transduction pathways are specificity, amplification of the signal, desensitisation and integration, which is accomplished not solely, but majorly by proteins. Array-based profiling of protein-protein and other biomolecular interactions is a versatile approach, which holds immense potential for multiplex interactome mapping and provides an inclusive representation of the signal transduction pathways and networks. Protein microarrays such as analytical protein microarrays (antigen-antibody interactions, autoantibody screening), RP microarrays (interaction of a particular ligand with all the possible targets in cell), functional protein microarrays (protein-protein or protein-ligand interactions) are implemented for various applications, including analysis of protein interactions and their significance in signalling cascades. Additionally, successful amalgamation of the array-based approaches with different label-free detection techniques allows real-time analysis of interaction kinetics of multiple interaction events simultaneously. This review discusses the prospects, merits and limitations of different variants of array-based techniques and their promising applications for studying the modifications and interactions of biomolecules, and highlights the studies associated with signal transduction pathways and their impact on disease pathobiology.

RNA polymerase II carboxyl-terminal domain (RNAPII CTD) phosphatases are a newly emerging family of phosphatases. Recently a CTD-specific phosphatase, small CTD phosphatase 1 (SCP1), has shown to act as an evolutionarily conserved transcriptional corepressor for inhibiting neuronal gene transcription in non-neuronal cells. In this study, using the established NIH/3T3 and HEK293T cells, which are expressing human SCP1 proteins under the tight control of expression by doxycycline, a proteomic screening was conducted to identify the binding partners for SCP1. Although the present findings provide the possibility for new avenues to provide to a better understanding of cellular physiology of SCP1, now these proteomic and some immunological approaches for SCP1 interactome might not represent the accurate physiological relevance in vivo. In this presentation, we focus the substrate specificity to delineate an appearance of the dephosphorylation reaction catalyzed by SCP1 phosphatase. We compared the phosphorylated sequences of the immunologically confirmed binding partners with SCP1 searched in HPRD. We found the similar sequences from CdcA3 and validated the efficiency of enzymatic catalysis for synthetic phosphopeptides the recombinant SCP1. This approach led to the identification of several interacting partners with SCP1. We suggest that CdcA3 could be an enzymatic substrate for SCP1 and that SCP1 might have the relationship with cell cycle regulation through enzymatic activity against CdcA3.