N-terminal truncated phospholipase A1 accessory protein PlaS from Serratia marcescens alleviates inhibitory on host cell growth and enhances PlaA1 enzymatic activity

Phospholipase A1 (PLA1) is a kind of specific phospholipid hydrolase widely used in food, medical, textile. However, limitations in its expression and enzymatic activity have prompted the investigation of the phospholipase-assisting protein PlaS. In this study, we elucidate the role of PlaS in enhancing the expression and activity of PlaA1 through N-terminal truncation. Our research demonstrates that truncating the N-terminal region of PlaS effectively overcomes its inhibitory effect on host cells, resulting in improved cell growth and increased protein solubility of the protein. The yeast two-hybrid assay confirms the interaction between PlaA1 and N-terminal truncated PlaS (∆N27 PlaS), highlighting their binding capabilities. Furthermore, in vitro studies using Biacore analysis reveal a concentration-dependent and specific binding between PlaA1 and ∆N27 PlaS, exhibiting high affinity. Molecular docking analysis provides insights into the hydrogen bond interactions between ∆N27 PlaS and PlaA1, identifying key amino acid residues crucial for their binding. Finally, the enzyme activity of PLA1 was boost to 8.4 U/mL by orthogonal test. Study significantly contributes to the understanding of the interaction mechanism between PlaS and PlaA1, offering potential strategies for enhancing PlaA1 activity through protein engineering approaches.

Revealing molecular determinants governing mambalgin-3 pharmacology at acid-sensing ion channel 1 variants

Acid-sensing ion channels (ASICs) are trimeric proton-gated cation channels that play a role in neurotransmission and pain sensation. The snake venom-derived peptides, mambalgins, exhibit potent analgesic effects in rodents by inhibiting central ASIC1a and peripheral ASIC1b. Despite their distinct species- and subtype-dependent pharmacology, previous structure-function studies have focussed on the mambalgin interaction with ASIC1a. Currently, the specific channel residues responsible for this pharmacological profile, and the mambalgin pharmacophore at ASIC1b remain unknown. Here we identify non-conserved residues at the ASIC1 subunit interface that drive differences in the mambalgin pharmacology from rat ASIC1a to ASIC1b, some of which likely do not make peptide binding interactions. Additionally, an amino acid variation below the core binding site explains potency differences between rat and human ASIC1. Two regions within the palm domain, which contribute to subtype-dependent effects for mambalgins, play key roles in ASIC gating, consistent with subtype-specific differences in the peptides mechanism. Lastly, there is a shared primary mambalgin pharmacophore for ASIC1a and ASIC1b activity, with certain peripheral peptide residues showing variant-specific significance for potency. Through our broad mutagenesis studies across various species and subtype variants, we gain a more comprehensive understanding of the pharmacophore and the intricate molecular interactions that underlie ligand specificity. These insights pave the way for the development of more potent and targeted peptide analogues required to advance our understating of human ASIC1 function and its role in disease.

CIP1, a CIPK23-interacting transporter, is implicated in Cd tolerance and phytoremediation

Environmental pollution from cadmium (Cd) presents a serious threat to plant growth and development. Therefore, it's crucial to find out how plants resist this toxic metal to develop strategies for remediating Cd-contaminated soils. In this study, we identified CIP1, a transporter protein, by screening interactors of the protein kinase CIPK23. CIP1 is located in vesicles membranes and can transport Cd2+ when expressed in yeast cells. Cd stress specifically induced the accumulation of CIP1 transcripts and functional proteins, particularly in the epidermal cells of the root tip. CIKP23 could interact directly with the central loop region of CIP1, phosphorylating it, which is essential for the efficient transport of Cd2+. A loss-of-function mutation of CIP1 in wild-type plants led to increased sensitivity to Cd stress. Conversely, tobacco plants overexpressing CIP1 exhibited improved Cd tolerance and increased Cd accumulation capacity. Interestingly, this Cd accumulation was restricted to roots but not shoots, suggesting that manipulating CIP1 does not risk Cd contamination of plants' edible parts. Overall, this study characterizes a novel Cd transporter, CIP1, with potential to enhance plant tolerance to Cd toxicity while effectively eliminating environmental contamination without economic losses.

High throughput methods to study protein-protein interactions during host-pathogen interactions

The ability of a pathogen to survive and cause an infection is often determined by specific interactions between the host and pathogen proteins. Such interactions can be both intra- and extracellular and may define the outcome of an infection. There are a range of innovative biochemical, biophysical and bioinformatic techniques currently available to identify protein-protein interactions (PPI) between the host and the pathogen. However, the complexity and the diversity of host-pathogen PPIs has led to the development of several high throughput (HT) techniques that enable the study of multiple interactions at once and/or screen multiple samples at the same time, in an unbiased manner. We review here the major HT laboratory-based technologies employed for host-bacterial interaction studies.

Proteomics analysis of differentially abundant proteins in the rohu kidney infected with Edwardsiella tarda

Edwardsiella tarda (Et) is a zoonotic gram-negative pathogen with a diverse host range, including fish. However, the in-depth molecular mechanisms underlying the response of Labeo rohita (rohu) kidney to Et are poorly understood. A proteomic and histopathological analysis was performed for the rohu kidney after Et infection. The histopathology of the infected rohu kidney showed vacuolation and necrosis. After LC-MS/MS analysis, ~1240 proteins were identified with ≥2 unique peptides. A total of 96 differentially abundant proteins (DAPs) were observed between the control and Et infected group (ET). Metascape and STRING analysis were used for the gene ontology (GO), and protein-protein interaction network (PPI) for the significant pathways of DAPs. In PPI, low-abundant proteins were mapped to metabolic pathways and oxidative phosphorylation (cox5ab, uqcrfs1). High-abundance proteins were mapped to ribosomes (rplp2), protein process in the ER (hspa8), and immune system (ptgdsb.1, muc2). Our label-free proteomic approach in the rohu kidney revealed abundant enriched proteins involved in vesicle coat (ehd4), complement activation (c3a.1, c9, c7a), phagosome (thbs4, mapk1), metabolic reprogramming (hao1, glud1a), wound healing (vim, alox5), and the immune system (psap) after Et infection. A targeted proteomics approach of multiple reaction monitoring (MRM) validated the DAPs (nprl3, ambp, vmo1a, hspg2, muc2, hao1 and glud1a) between control and ET. Overall, the current analysis of histology and proteome in the rohu kidney provides comprehensive data on pathogenicity and the potential immune proteins against Et.

Molecular recognition and interaction between human plasminogen Kringle 5 and A2M domain in human complement C5 by biospecific methods coupled with molecular dynamics simulation

The potent angiogenesis inhibitor known as human plasminogen Kringle 5 has shown promise in the treatment of vascular disorders and malignancies. The study aimed to investigate the recognition and interaction between Kringle 5 and the A2M domain of human complement component C5 using bio-specific methodologies and molecular dynamics (MD) simulation. Initially, the specific interaction between Kringle 5 and A2M was confirmed and characterized through Ligand Blot and ELISA, yielding the dissociation constant (Kd) of 1.70 × 10-7 mol/L. Then, Kringle 5 showcased a dose-dependent inhibition of the production of C5a in lung cancer A549 cells, consequently impeding their proliferation and migration. Following the utilization of frontal affinity chromatography (FAC), it was revealed that there exists a singular binding site with the binding constant (Ka) of 3.79 × 105 L/mol. Following the implementation of homology modeling and MD optimization, the detailed results indicate that only a specific segment of the N-terminal structure of the A2M molecule engages in interaction with Kringle 5 throughout the binding process and the principal driving forces encompass electrostatic force, hydrogen bonding, and van der Waals force. In conclusion, the A2M domain of human complement C5 emerges as a plausible binding target for Kringle 5 in vivo.

WSSV early protein WSSV004 enhances viral replication by suppressing LDH activity

White spot syndrome virus (WSSV) is known to upregulate glycolysis to supply biomolecules and energy for the virus's replication. At the viral genome replication stage, lactate dehydrogenase (LDH), a glycolytic enzyme, shows increased activity without any increase in expression. In the present study, yeast 2-hybrid screening was used to identify WSSV proteins that interacted with LvLDH isoform 1 and 2, and these included the WSSV early protein WSSV004. The interaction between WSSV004 and LvLDH1/2 was confirmed by co-immunoprecipitation. Immunofluorescence showed that WSSV004 co-localized with LvLDH1/2 in the cytoplasm. dsRNA silencing experiments showed that WSSV004 was crucial for WSSV replication. However, although WSSV004 silencing led to the suppression of total LvLDH gene expression during the viral late stage, there was nevertheless a significant increase in LvLDH activity at this time. We also used affinity purification-mass spectrometry to identify cellular proteins that interact with WSSV004, and found a total of 108 host proteins and 3 WSSV proteins with which it potentially interacts. Bioinformatics analysis revealed that WSSV004 and its interacting proteins might be responsible for various biological pathways during infection, including vesicular transport machinery and RNA-related functions. Collectively, our study suggests that WSSV004 serves as a multifunctional modulator to facilitate WSSV replication.

A protein-protein interaction network aligner study in the multi-objective domain

BACKGROUND AND OBJECTIVE

The protein-protein interaction (PPI) network alignment has proven to be an efficient technique in the diagnosis and prevention of certain diseases. However, the difficulty in maximizing, at the same time, the two qualities that measure the goodness of alignments (topological and biological quality) has led aligners to produce very different alignments. Thus making a comparative study among alignments of such different qualities a big challenge. Multi-objective optimization is a computer method, which is very powerful in this kind of contexts because both conflicting qualities are considered together. Analysing the alignments of each PPI network aligner with multi-objective methodologies allows you to visualize a bigger picture of the alignments and their qualities, obtaining very interesting conclusions. This paper proposes a comprehensive PPI network aligner study in the multi-objective domain.

METHODS

Alignments from each aligner and all aligners together were studied and compared to each other via Pareto dominance methodologies. The best alignments produced by each aligner and all aligners together for five different alignment scenarios were displayed in Pareto front graphs. Later, the aligners were ranked according to the topological, biological, and combined quality of their alignments. Finally, the aligners were also ranked based on their average runtimes.

RESULTS

Regarding aligners constructing the best overall alignments, we found that SAlign, BEAMS, SANA, and HubAlign are the best options. Additionally, the alignments of best topological quality are produced by: SANA, SAlign, and HubAlign aligners. On the contrary, the aligners returning the alignments of best biological quality are: BEAMS, TAME, and WAVE. However, if there are time constraints, it is recommended to select SAlign to obtain high topological quality alignments and PISwap or SAlign aligners for high biological quality alignments.

CONCLUSIONS

The use of the SANA aligner is recommended for obtaining the best alignments of topological quality, BEAMS for alignments of the best biological quality, and SAlign for alignments of the best combined topological and biological quality. Simultaneously, SANA and BEAMS have above-average runtimes. Therefore, it is suggested, if necessary due to time restrictions, to choose other, faster aligners like SAlign or PISwap whose alignments are also of high quality.

Elucidating the interaction mechanism of rice glutelin and soybean 11S globulin using multi-spectroscopy and molecular dynamics simulation methods

Rice gluten, as the hydrophobic protein, exhibits restricted application value in hydrophilic food, which may be enhanced through interaction with soybean 11S globulin, characterized by favorable functional properties. This study aims at revealing their interaction mechanism via multi-spectroscopy and molecular dynamics simulation. The formation and structural change of rice glutelin-soybean 11S globulin complexes were detected using fluorescence, ultra-violet and circular dichroism spectra. The addition of 11S globulin increased the contents of α-helix, β-turn and random coil, but decreased β-sheet content, and the change in secondary structure was correlated with particle size. Moreover, exposure of hydrophobic groups and formation of disulfide bonds occurred in the complexes. Molecular dynamics simulation verified these experimental results through analyses of root mean square deviation and fluctuation, hydrogen bond, secondary structure, and binding free energy analysis. This study contributes to expounding the interaction mechanism of protein and protein from the molecular level.

Identifying allergic-rhinitis-associated genes with random-walk-based method in PPI network

Allergic rhinitis is a common allergic disease with a complex pathogenesis and many unresolved issues. Studies have shown that the incidence of allergic rhinitis is closely related to genetic factors, and research on the related genes could help further understand its pathogenesis and develop new treatment methods. In this study, 446 allergic rhinitis-related genes were obtained on the basis of the DisGeNET database. The protein-protein interaction network was searched using the random-walk-with-restart algorithm with these 446 genes as seed nodes to assess the linkages between other genes and allergic rhinitis. Then, this result was further examined by three screening tests, including permutation, interaction, and enrichment tests, which aimed to pick up genes that have strong and special associations with allergic rhinitis. 52 novel genes were finally obtained. The functional enrichment test confirmed their relationships to the biological processes and pathways related to allergic rhinitis. Furthermore, some genes were extensively analyzed to uncover their special or latent associations to allergic rhinitis, including IRAK2 and MAPK, which are involved in the pathogenesis of allergic rhinitis and the inhibition of allergic inflammation via the p38-MAPK pathway, respectively. The new found genes may help the following investigations for understanding the underlying molecular mechanisms of allergic rhinitis and developing effective treatments.

USP7 interacts with and destabilizes oncoprotein SET

Oncoprotein SE translocation (SET) is frequently overexpressed in different types of tumors and correlated with poor prognosis of cancer patients. Targeting SET has been considered a promising strategy for cancer intervention. However, the mechanisms by which SET is regulated under cellular conditions are largely unknown. Here, by performing a tandem affinity purification-mass spectrometry (TAP-MS), we identify that the ubiquitin-specific protease 7 (USP7) forms a stable protein complex with SET in cancer cells. Further analyses reveal that the acidic domain of SET directly binds USP7 while both catalytic domain and ubiquitin-like (UBL) domains of USP7 are required for SET binding. Knockdown of USP7 has no effect on the mRNA level of SET. However, we surprisingly find that USP7 depletion leads to a dramatic elevation of SET protein levels, suggesting that USP7 plays a key role in destabilizing oncoprotein SET, possibly through an indirect mechanism. To our knowledge, our data report the first deubiquitinase (DUB) that physically associates with oncoprotein SET and imply an unexpected regulatory effect of USP7 on SET stability.

A bioinformatics approach to systematically analyze the molecular patterns of monkeypox virus-host cell interactions

Monkeypox has been spreading worldwide since May 2022, when the World Health Organization (WHO) declared the outbreak a "public health emergency of international concern." The spread of monkeypox has posed a serious threat to the health of people around the world, but few studies have been conducted, and the molecular mechanism of monkeypox after infection remains unclear. We therefore implemented a transcriptome analysis to identify signaling pathways and biomarkers in monkeypox-infected cells to help understand monkeypox-host cell interactions. In this study, datasets GSE36854 and GSE11234 were obtained from GEO. Of these, 84 significantly different genes were identified in the dataset GSE36854, followed by KEGG, GO analysis protein-protein interaction (PPI) construction, and Hub gene extraction. We also analyzed the expression regulation of hub genes and screened for drugs targeting hub genes. The results showed that monkeypox-infected cells significantly activated the cellular immune response. The top 10 hub genes are IER3, IFIT2, IL11, ZC3H12A, EREG, IER2, NFKBIE, FST, IFIT1 and AREG. AP-26113 and itraconazole can be used to counteract the inhibitory effect of monkeypox on IFIT1 and IFIT2 and serve as candidate drugs for the treatment of monkeypox virus infection. IRF1 may also be a transcription factor of IFIT. Our results provide a new entry point for understanding how monkeypox virus interacts with its host.

[Network science. Part 1 : in oncology in general]

The overwhelming avalanche of data issued from the omics cascade, and particularly the mapping of protein-protein interaction (interactome), allows us to dissect the complexity and overlapping of diseases, as well as their management. With the help of theoretical and scientific bases issued form network science, as well as the rapid evolution of artificial intelligence, in particular machine learning (with its high speed and capacity), we are able today to uncover new driver genes, new biomarkers, new interactions with diagnostic and therapeutic modalities (even for an individual patient). It also opens new perspectives in the fields of prediction of response to treatment as well as prevention. The expectations are particularly high and diverse in health care. We take stock non-exhaustively on some applications in the field of oncology.

Order wrapped in chaos: On the roles of intrinsically disordered proteins and RNAs in the arrangement of the mitochondrial enzymatic machines

The analysis of cryo-electron tomography images of human and rat mitochondria revealed that the mitochondrial matrix is at least as crowded as the cytosol. To mitigate the crowding effects, metabolite transport in the mitochondria primarily occurs through the intermembrane space, which is significantly less crowded. The scientific literature largely ignores how enzyme systems and metabolite transport are organized in the crowded environment of the mitochondrial matrix. Under crowded conditions, multivalent interactions carried out by disordered protein regions (IDRs), may become extremely important. We analyzed the human mitochondrial proteome to determine the presence and physiological significance of IDRs. Despite mitochondrial proteins being generally more ordered than cytosolic or overall proteome proteins, disordered regions plays a significant role in certain mitochondrial compartments and processes. Even in highly ordered enzyme systems, there are proteins with long IDRs. Some IDRs act as binding elements between highly ordered subunits, while the roles of others are not yet established. Mitochondrial systems, like their bacterial ancestors, rely less on IDRs and more on RNA for LLPS compartmentalization. More evolutionarily advanced subsystems that enable mitochondria-cell interactions contain more IDRs. The study highlights the crucial and often overlooked role played by IDRs and non-coding RNAs in mitochondrial organization.

PDZome-wide and structural characterization of the PDZ-binding motif of VANGL2

VANGL2 is a core component of the non-canonical Wnt/Planar Cell Polarity signaling pathway that uses its highly conserved carboxy-terminal type 1 PDZ-binding motif (PBM) to bind a variety of PDZ proteins. In this study, we characterize and quantitatively assess the largest VANGL2 PDZome-binding profile documented so far, using orthogonal methods. The results of our holdup approach support VANGL2 interactions with a large panel of both long-recognized and unprecedented PDZ domains. Truncation and point mutation analyses of the VANGL2 PBM establish that, beyond the strict requirement of the P-0 / V521 and P-2 / T519 amino acids, upstream residues, including E518, Q516 and R514 at, respectively, P-3, P-5 and P-7 further contribute to the robustness of VANGL2 interactions with two distinct PDZ domains, SNX27 and SCRIBBLE-PDZ3. In agreement with these data, incremental amino-terminal deletions of the VANGL2 PBM causes its overall affinity to progressively decline. Moreover, the holdup data establish that the PDZome binding repertoire of VANGL2 starts to diverge significantly with the truncation of E518. A structural analysis of the SYNJ2BP-PDZ/VANGL2 interaction with truncated PBMs identifies a major conformational change in the binding direction of the PBM peptide after the P-2 position. Finally, we report that the PDZome binding profile of VANGL2 is dramatically rearranged upon phosphorylation of S517, T519 and S520. Our crystallographic approach illustrates how SYNJ2BP accommodates a S520-phosphorylated PBM peptide through the ideal positioning of two basic residues, K48 and R86. Altogether our data provides a comprehensive view of the VANGL2 PDZ network and how this network specifically responds to the post-translation modification of distinct PBM residues. These findings should prove useful in guiding future functional and molecular studies of the key PCP component VANGL2.

Oligo-benzamide-based peptide mimicking tools for modulating biology

The oligo-benzamide scaffold is a rigid organic framework that can hold 2-3 functional groups as O-alkyl substituents on its benzamide units, mirroring their natural arrangement in an α-helix. Oligo-benzamides demonstrated outstanding α-helix mimicry and can be readily synthesized by following high yielding and iterative reaction steps in both solution-phase and solid-phase. A number of oligo-benzamides have been designed to emulate α-helical peptide segments in biologically active proteins and showed strong protein binding, in turn effectively disrupting protein-protein interactions in vitro and in vivo. In this chapter, the design of oligo-benzamides for mimicking α-helices, efficient synthetic routes for producing them, and their biomedical studies showing remarkable potency in inhibiting protein functions are discussed.

Analysis and prediction of interactions between transmembrane and non-transmembrane proteins

BACKGROUND

Most of the important biological mechanisms and functions of transmembrane proteins (TMPs) are realized through their interactions with non-transmembrane proteins(nonTMPs). The interactions between TMPs and nonTMPs in cells play vital roles in intracellular signaling, energy metabolism, investigating membrane-crossing mechanisms, correlations between disease and drugs.

RESULTS

Despite the importance of TMP-nonTMP interactions, the study of them remains in the wet experimental stage, lacking specific and comprehensive studies in the field of bioinformatics. To fill this gap, we performed a comprehensive statistical analysis of known TMP-nonTMP interactions and constructed a deep learning-based predictor to identify potential interactions. The statistical analysis describes known TMP-nonTMP interactions from various perspectives, such as distributions of species and protein families, enrichment of GO and KEGG pathways, as well as hub proteins and subnetwork modules in the PPI network. The predictor implemented by an end-to-end deep learning model can identify potential interactions from protein primary sequence information. The experimental results over the independent validation demonstrated considerable prediction performance with an MCC of 0.541.

CONCLUSIONS

To our knowledge, we were the first to focus on TMP-nonTMP interactions. We comprehensively analyzed them using bioinformatics methods and predicted them via deep learning-based solely on their sequence. This research completes a key link in the protein network, benefits the understanding of protein functions, and helps in pathogenesis studies of diseases and associated drug development.

Evaluation of network-guided random forest for disease gene discovery

BACKGROUND

Gene network information is believed to be beneficial for disease module and pathway identification, but has not been explicitly utilized in the standard random forest (RF) algorithm for gene expression data analysis. We investigate the performance of a network-guided RF where the network information is summarized into a sampling probability of predictor variables which is further used in the construction of the RF.

RESULTS

Our simulation results suggest that network-guided RF does not provide better disease prediction than the standard RF. In terms of disease gene discovery, if disease genes form module(s), network-guided RF identifies them more accurately. In addition, when disease status is independent from genes in the given network, spurious gene selection results can occur when using network information, especially on hub genes. Our empirical analysis on two balanced microarray and RNA-Seq breast cancer datasets from The Cancer Genome Atlas (TCGA) for classification of progesterone receptor (PR) status also demonstrates that network-guided RF can identify genes from PGR-related pathways, which leads to a better connected module of identified genes.

CONCLUSIONS

Gene networks can provide additional information to aid the gene expression analysis for disease module and pathway identification. But they need to be used with caution and validation on the results need to be carried out to guard against spurious gene selection. More robust approaches to incorporate such information into RF construction also warrant further study.

Sinapine targeting PLCβ3 EF hands disrupts Gαq-PLCβ3 interaction and ameliorates cardiovascular diseases

BACKGROUND

The renin-angiotensin-aldosterone system (RAAS) over-activation is highly involved in cardiovascular diseases (CVDs), with the Gαq-PLCβ3 axis acting as a core node of RAAS. PLCβ3 is a potential target of CVDs, and the lack of inhibitors has limited its drug development.

PURPOSE

Sinapine (SP) is a potential leading compound for treating CVDs. Thus, we aimed to elucidate the regulation of SP towards the Gαq-PLCβ3 axis and its molecular mechanism.

STUDY DESIGN

Aldosteronism and hypertension animal models were employed to investigate SP's inhibitory effect on the abnormal activation of the RAAS through the Gαq-PLCβ3 axis. We used chemical biology methods to identify potential targets and elucidate the underlying molecular mechanisms.

METHODS

The effects of SP on aldosteronism and hypertension were evaluated using an established animal model in our laboratory. Target identification and underlying molecular mechanism research were performed using activity-based protein profiling with a bio-orthogonal click chemistry reaction and other biochemical methods.

RESULTS

SP alleviated aldosteronism and hypertension in animal models by targeting PLCβ3. The underlying mechanism for blocking the Gαq-PLCβ3 interaction involves targeting the EF hands through the Asn-260 amino acid residue. SP regulated the Gαq-PLCβ3 axis more precisely than the Gαq-GEFT or Gαq-PKCζ axis in the cardiovascular system.

CONCLUSION

SP alleviated RAAS over-activation via Gαq-PLCβ3 interaction blockade by targeting the PLCβ3 EF hands domain, which provided a novel PLC inhibitor for treating CVDs. Unlike selective Gαq inhibitors, SP reduced the risk of side effects compared to Gαq inhibitors in treating CVDs.

TBX15 and SDHB expression changes in colorectal cancer serve as potential prognostic biomarkers

Alterations in the expression of certain genes could be associated with both patient mortality rates and drug resistance. This study aimed to identify genes in colorectal cancer (CRC) that potentially serve as hub genes influencing patient survival rates. RNA-Seq data were downloaded from the cancer genome atlas database, and differential expression analysis was performed between tumors and healthy controls. Through the utilization of univariate and multivariate Cox regression analyses, in combination with the MCODE clustering module, the genes whose expression changes were related to survival rate and the hub genes related to them were identified. The mortality risk model was computed using the hub genes. CRC samples and the RT-qPCR method were utilized to confirm the outcomes. PharmacoGx data were employed to link the expression of potential genes to medication resistance and sensitivity. The results revealed the discovery of seven hub genes, which emerged as independent prognostic markers. These included HOXC6, HOXC13, HOXC8, and TBX15, which were associated with poor prognosis and overexpression, as well as SDHB, COX5A, and UQCRC1, linked to favorable prognosis and downregulation. Applying the risk model developed with the mentioned genes revealed a markedly higher incidence of deceased patients in the high-risk group compared to the low-risk group. RT-qPCR results indicated a decrease in SDHB expression and an elevation in TBX15 levels in cancer samples relative to adjacent healthy tissue. Also, PharmacoGx data indicated that the expression level of SDHB was correlated with drug sensitivity to Crizotinib and Dovitinib. Our findings highlight the potential association between alterations in the expression of genes such as HOXC6, HOXC13, HOXC8, TBX15, SDHB, COX5A, and UQCRC1 and increased mortality rates in CRC patients. As revealed by the PPI network, these genes exhibited the most connections with other genes linked to survival.

Identification and functional characterization of putative ligand binding domain(s) of JlpA protein of Campylobacter jejuni

Among the major Surface Exposed Colonization Proteins (SECPs) of Campylobacter jejuni (C. jejuni), Jejuni lipoprotein A (JlpA) plays a crucial role in host cell adhesion specifically by binding to the N-terminal domain of the human heat shock protein 90α (Hsp90α-NTD). Although the JlpA binding to Hsp90α activates NF-κB and p38 MAP kinase pathways, the underlying mechanism of JlpA association with the cellular receptor remains unclear. To this end, we predicted two potential receptor binding sites within the C-terminal domain of JlpA: one spanning from amino acid residues Q332-A354 and the other from S258-T295; however, the latter exhibited weaker binding. To assess the functional attributes of these predicted sequences, we generated two JlpA mutants (JlpAΔ1: S258-T295; JlpAΔ2: Q332-A354) and assessed the Hsp90α-binding affinity-kinetics by in vitro and ex vivo experiments. Our findings confirmed that the residues Q332-A354 are of greater importance in host cell adhesion with a measurable impact on cellular responses. Further, thermal denaturation by circular dichroism (CD) confirmed that the reduced binding affinity of the JlpAΔ2 to Hsp90α is not associated with protein folding or stability. Together, this study provides a possible framework for determining the molecular function of designing rational inhibitors efficiently targeting JlpA.

Molecular insights on the coronavirus MERS-CoV interaction with the CD26 receptor

The Middle East respiratory syndrome (MERS) is a severe respiratory disease with high fatality rates, caused by the Middle East respiratory syndrome coronavirus (MERS-CoV). The virus initiates infection by binding to the CD26 receptor (also known as dipeptidyl peptidase 4 or DPP4) via its spike protein. Although the receptor-binding domain (RBD) of the viral spike protein and the complex between RBD and the extracellular domain of CD26 have been studied using X-ray crystallography, conflicting studies exist regarding the importance of certain amino acids outside the resolved RBD-CD26 complex interaction interface. To gain atomic-level knowledge of the RBD-CD26 complex, we employed computational simulations to study the complex's dynamic behavior as it evolves from its crystal structure to a conformation stable in solution. Our study revealed previously unidentified interaction regions and interacting amino acids within the complex, determined a novel comprehensive RBD-binding domain of CD26, and by that expanded the current understanding of its structure. Additionally, we examined the impact of a single amino acid substitution, E513A, on the complex's stability. We discovered that this substitution disrupts the complex through an allosteric domino-like mechanism that affects other residues. Since MERS-CoV is a zoonotic virus, we evaluated its potential risk of human infection via animals, and suggest a low likelihood for possible infection by cats or dogs. The molecular structural information gleaned from our insights into the RBD-CD26 complex pre-dissociative states may be proved useful not only from a mechanistic view but also in assessing inter-species transmission and in developing anti-MERS-CoV antiviral therapeutics.

Personalized Protein-Protein Interaction Networks Towards Unraveling the Molecular Mechanisms of Alzheimer's Disease

Alzheimer's disease (AD) is a highly heterogenous neurodegenerative disease, and several omic-based datasets were generated in the last decade from the patients with the disease. However, the vast majority of studies evaluate these datasets in bulk by considering all the patients as a single group, which obscures the molecular differences resulting from the heterogeneous nature of the disease. In this study, we adopted a personalized approach and analyzed the transcriptome data from 403 patients individually by mapping the data on a human protein-protein interaction network. Patient-specific subnetworks were discovered and analyzed in terms of the genes in the subnetworks, enriched functional terms, and known AD genes. We identified several affected pathways that could not be captured by the bulk comparison. We also showed that our personalized findings point to patterns of alterations consistent with the recently suggested AD subtypes.

Identification of key genes and immune infiltration in osteoarthritis through analysis of zinc metabolism-related genes

BACKGROUND

Osteoarthritis (OA) represents a prominent etiology of considerable pain and disability, and conventional imaging methods lack sensitivity in diagnosing certain types of OA. Therefore, there is a need to identify highly sensitive and efficient biomarkers for OA diagnosis. Zinc ions feature in the pathogenesis of OA. This work aimed to investugate the role of zinc metabolism-related genes (ZMRGs) in OA and the diagnostic characteristics of key genes.

METHODS

We obtained datasets GSE169077 and GSE55235 from the Gene Expression Omnibus (GEO) and obtained ZMRGs from MSigDB. Differential expression analysis was conducted on the GSE169077 dataset using the limma R package to identify differentially expressed genes (DEGs), and the intersection of DEGs and ZMRGs yielded zinc metabolism differential expression-related genes (ZMRGs-DEGs). The clusterProfiler R package was employed for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of ZMRGs-DEGs. Potential small molecule drugs were predicted using the CMap database, and immune cell infiltration and function in OA individuals were analyzed using the ssGSEA method. Protein-protein interaction (PPI) networks were constructed to detect Hub genes among ZMRGs-DEGs. Hub gene expression levels were analyzed in the GSE169077 and GSE55235 datasets, and their diagnostic characteristics were assessed using receiver operating characteristic (ROC) curves. The gene-miRNA interaction network of Hub genes was explored using the gene-miRNA interaction network website.

RESULTS

We identified 842 DEGs in the GSE169077 dataset, and their intersection with ZMRGs resulted in 46 ZMRGs-DEGs. ZMRGs-DEGs were primarily enriched in functions such as collagen catabolic processes, extracellular matrix organization, metallopeptidase activity, and pathways like the IL-17 signaling pathway, Nitrogen metabolism, and Relaxin signaling pathway. Ten potential small-molecule drugs were predicted using the CMap database. OA patients exhibited distinct immune cell abundance and function compared to healthy individuals. We identified 4 Hub genes (MMP2, MMP3, MMP9, MMP13) through the PPI network, which were highly expressed in OA and demonstrated good diagnostic performance. Furthermore, two closely related miRNAs for each of the 4 Hub genes were identified.

CONCLUSION

4 Hub genes were identified as potential diagnostic biomarkers and therapeutic targets for OA.

Rubisco Accumulation Factor1-like (RAFL) interacts with RAF1 to mediate Rubisco assembly in Arabidopsis

Rubisco catalysis a rate-limiting step in photosynthesis. It is a complex of eight large (RbcL) and eight small (RbcS) subunits. The biogenesis of Rubisco requires assembly chaperones. One of the key Rubisco assembly chaperones, Rubisco accumulation factor1 (RAF1), assembled as a dimer, acts downstream of chaperonin-assisted RbcL folding by stabilizing RbcL antiparallel dimers for assembly into RbcL8 complexes. In maize, lacking RAF1 causes Rubisco deficient and seedling lethal. A RAF1 homologue, RAF1-like (RAFL), has been detected in Arabidopsis. We found RAFL shares 61.98 % sequence similarity with RAF1. They have similar conserved domains, predicted 3D structures and gene expression pattern. Phylogenetic tree analysis showed that RAFL and RAF1 only present in analyzed dicots, while only one copy of RAF presented in monocots, mosses and green algae. Combined analysis by three different protein-protein interaction methods showed that RAFL interacts with RAF1 both in vivo and in vitro. Taken together, we conclude that RAFL and RAF1 are close paralogous genes, and they can form heterodimer and/or homodimers to mediate Rubisco assembly in Arabidopsis.