Protein Structure Analysis Research Articles

Characterization of FBA genes in potato (Solanum tuberosum L.) and expression patterns in response to light spectrum and abiotic stress.

Fructose-1, 6-bisphosphate aldolase (FBA) plays vital roles in plant growth, development, and response to abiotic stress. However, genome-wide identification and structural characterization of the potato (Solanum tuberosum L.) FBA gene family has not been systematically analyzed. In this study, we identified nine StFBA gene members in potato, with six StFBA genes localized in the chloroplast and three in the cytoplasm. The analysis of gene structures, protein structures, and phylogenetic relationships indicated that StFBA genes were divided into Class I and II, which exhibited significant differences in structure and function. Synteny analysis revealed that segmental duplication events promoted the expansion of the StFBA gene family. Promoter analysis showed that most StFBA genes contained cis-regulatory elements associated with light and stress responses. Expression analysis showed that StFBA3, StFBA8, and StFBA9 showing significantly higher expression levels in leaf, stolon, and tuber under blue light, indicating that these genes may improve photosynthesis and play an important function in regulating the induction and expansion of microtubers. Expression levels of the StFBA genes were influenced by drought and salt stress, indicating that they played important roles in abiotic stress. This work offers a theoretical foundation for in-depth understanding of the evolution and function of StFBA genes, as well as providing the basis for the genetic improvement of potatoes.

Boosting Clear Cell Renal Carcinoma-Specific Drug Discovery Using a Deep Learning Algorithm and Single-Cell Analysis.

Clear cell renal carcinoma (ccRCC), the most common subtype of renal cell carcinoma, has the high heterogeneity of a highly complex tumor microenvironment. Existing clinical intervention strategies, such as target therapy and immunotherapy, have failed to achieve good therapeutic effects. In this article, single-cell transcriptome sequencing (scRNA-seq) data from six patients downloaded from the GEO database were adopted to describe the tumor microenvironment (TME) of ccRCC, including its T cells, tumor-associated macrophages (TAMs), endothelial cells (ECs), and cancer-associated fibroblasts (CAFs). Based on the differential typing of the TME, we identified tumor cell-specific regulatory programs that are mediated by three key transcription factors (TFs), whilst the TF EPAS1/HIF-2α was identified via drug virtual screening through our analysis of ccRCC's protein structure. Then, a combined deep graph neural network and machine learning algorithm were used to select anti-ccRCC compounds from bioactive compound libraries, including the FDA-approved drug library, natural product library, and human endogenous metabolite compound library. Finally, five compounds were obtained, including two FDA-approved drugs (flufenamic acid and fludarabine), one endogenous metabolite, one immunology/inflammation-related compound, and one inhibitor of DNA methyltransferase (N4-methylcytidine, a cytosine nucleoside analogue that, like zebularine, has the mechanism of inhibiting DNA methyltransferase). Based on the tumor microenvironment characteristics of ccRCC, five ccRCC-specific compounds were identified, which would give direction of the clinical treatment for ccRCC patients.

Production of 14α-Hydroxy Progesterone Using a Steroidal Hydroxylase from Cochliobolus lunatus Expressed in Escherichia coli

Steroids with hydroxylation at C14 are drawing increased attention because of their diverse biological activities and applications. P-450lun from Cochliobolus lunatus is the first fungal cytochrome P450 reported to have 14α-hydroxylase activity. Studies have shown that P-450lun catalyzes the hydroxylation of progesterone (PROG) at C14α with low regiospecificity and activity. To improve its regiospecificity and activity for PROG, truncated forms of P-450lun and its cognate redox partner CPRlun were functionally co-expressed in Escherichia coli. Then, a semi-rational protein engineering approach was applied to P-450lun, resulting in a double-site mutant E109A/F297W with enhanced 14α-position selectivity for PROG compared with the wild-type P-450lun (97% vs. 28%). Protein structure analysis revealed that the F297W substitution can hinder the binding pose for 11β-hydroxylation product formation. Finally, whole-cell catalysis was optimized, and the final titer of 14α-OH-PROG reached 16.0 mg/L. This is the first report where a fungal 14α-hydroxylase was functionally expressed in Escherichia coli. The steroid hydroxylation system obtained in this study can serve as a basis for the synthesis of 14α-hydroxylated PROG and the rapid evolution of eukaryotic cytochrome P-450lun.

Insights from the SNP analysis of TYMP gene linking MNGIE.

TYMP gene, which codes for thymidine phosphorylase (TP) is also known as platelet-derived endothelial cell growth factor (PD-ECGF). TP plays crucial roles in nucleotide metabolism and angiogenesis. Mutations in the TYMP gene can lead to Mitochondrial Neurogastrointestinal Encephalopathy (MNGIE) syndrome, a rare genetic disorder. Our main objective was to evaluate the impact of detrimental non-synonymous single nucleotide polymorphisms (nsSNPs) on TP protein structure and predict harmful variants in untranslated regions (UTR). We employed a combination of predictive algorithms to identify nsSNPs with potential deleterious effects, followed by molecular modeling analysis to understand their effects on protein structure and function. Using 13 algorithms, we identified 119 potentially deleterious nsSNPs, with 82 located in highly conserved regions. Of these, 53 nsSNPs were functional and exposed, while 79 nsSNPs reduced TP protein stability. Further analysis of 18 nsSNPs through 3D protein structure analysis revealed alterations in amino acid interactions, indicating their potential impact on protein function. This will help in the development of faster and more efficient genetic tests for detecting TYMP gene mutations.

Structural and biochemical analysis of penicillin-binding protein 2 from Campylobacter jejuni

Penicillin-binding protein 2 (PBP2) plays a key role in the formation of peptidoglycans in bacterial cell walls by crosslinking glycan chains through transpeptidase activity. PBP2 is also found in Campylobacter jejuni, a pathogenic bacterium that causes food-borne enteritis in humans. To elucidate the essential structural features of C. jejuni PBP2 (cjPBP2) that mediate its biological function, we determined the crystal structure of cjPBP2 and assessed its protein stability under various conditions. cjPBP2 adopts an elongated two-domain structure, consisting of a transpeptidase domain and a pedestal domain, and contains typical active site residues necessary for transpeptidase activity, as observed in other PBP2 proteins. Moreover, cjPBP2 responds to β-lactam antibiotics, including ampicillin, cefaclor, and cefmetazole, suggesting that β-lactam antibiotics inactivate cjPBP2. In contrast to typical PBP2 proteins, cjPBP2 is a rare example of a Zn2+-binding PBP2 protein, as the terminal structure of its transpeptidase domain accommodates a Zn2+ ion via three cysteine residues and one histidine residue. Zn2+ binding helps improve the protein stability of cjPBP2, providing opportunities to develop new C. jejuni-specific antibacterial drugs that counteract the Zn2+-binding ability of cjPBP2.

Sequence-based design and construction of synthetic nanobody library.

Nanobody (Nb), the smallest antibody fragments known to bind antigens, is now widely applied to various studies, including protein structure analysis, bioassay, diagnosis, and biomedicine. The traditional approach to generating specific nanobodies involves animal immunization which is time-consuming and expensive. As the understanding of the antibody repertoire accumulation, the synthetic library, which is devoid of animals, has attracted attention widely in recent years. Here, we describe a synthetic phage display library (S-Library), designed based on the systematic analysis of the next-generation sequencing (NGS) of nanobody repertoire. The library consists of a single highly conserved scaffold (IGHV3S65*01-IGHJ4*01) and complementary determining regions of constrained diversity. The S-Library containing 2.19 × 108 independent clones was constructed by the one-step assembly and rapid electro-transformation. The S-Library was screened against various targets (Nb G8, fusion protein of Nb G8 and green fluorescent protein, bovine serum albumin, ovalbumin, and acetylcholinesterase). In comparison, a naïve library (N-Library) from the source of 13 healthy animals was constructed and screened against the same targets as the S-Library. Binders were isolated from both S-Library and N-Library. The dynamic affinity was evaluated by the biolayer interferometry. The data confirms that the feature of the Nb repertoire is conducive to reducing the complexity of library design, thus allowing the S-Library to be built on conventional reagents and primers.

Platelet proteomic profiling in sitosterolemia suggests thrombocytopenia is driven by lipid disorder and not platelet aberrations

AbstractSitosterolemia is a rare autosomal recessive genetic disorder in which patients develop hypercholesterolemia and may exhibit abnormal hematologic and/or liver test results. In this disease, dysfunction of either ABCG5 or ABCG8 results in the intestinal hyperabsorption of all sterols, including cholesterol and, more specifically, plant sterols or xenosterols, as well as in the impaired ability to excrete xenosterols into the bile. It remains unknown how and why some patients develop hematologic abnormalities. Only a few unrelated patients with hematologic abnormalities at the time of diagnosis have been reported. Here, we report on 2 unrelated pedigrees who were believed to have chronic immune thrombocytopenia as their most prominent feature. Both consanguineous families showed recessive gene variants in ABCG5, which were associated with the disease by in silico protein structure analysis and clinical segregation. Hepatosplenomegaly was absent. Thrombopoietin levels and megakaryocyte numbers in the bone marrow were normal. Metabolic analysis confirmed the presence of strongly elevated plasma levels of xenosterols. Potential platelet proteomic aberrations were longitudinally assessed following dietary restrictions combined with administration of the sterol absorption inhibitor ezetimibe. No significant effects on platelet protein content before and after the onset of treatment were demonstrated. Although we cannot exclude that lipotoxicity has a direct and platelet-specific impact in patients with sitosterolemia, our data suggest that thrombocytopenia is neither caused by a lack of megakaryocytes nor driven by proteomic aberrations in the platelets themselves.

Structural and sequence analysis of the RPO30 gene of sheeppox and goatpox viruses from India

Sheeppox and goatpox are transboundary viral diseases of sheep and goats that cause significant economic losses to small and marginal farmers worldwide, including India. Members of the genus Capripoxvirus (CaPV), namely Sheeppox virus (SPPV), Goatpox virus (GTPV), and Lumpy skin disease virus (LSDV), are antigenically similar, and species differentiation can only be accomplished using molecular approaches. The present study aimed to understand the molecular epidemiology and host specificity of SPPV and GTPV circulating in India through sequencing and structural analysis of the RNA polymerase subunit-30 kDa (RPO30) gene. A total of 29 field isolates from sheep (n = 19) and goats (n = 10) belonging to different geographical regions of India during the period: Year 2015 to 2023, were analyzed based on the sequence and structure of the full-length RPO30 gene/protein. Phylogenetically, all the CaPV isolates were separated into three major clusters: SPPV, GTPV, and LSDV. Multiple sequence alignment revealed a highly conserved RPO30 gene, with a stretch of 21 nucleotide deletion in all SPPV isolates. Additionally, the RPO30 gene of the Indian SPPV and GTPV isolates possessed several species-specific conserved signature residues/motifs that could act as genotyping markers. Secondary structure analysis of the RPO30 protein showed four α-helices, two loops, and three turns, similar to that of the E4L protein of vaccinia virus (VACV). All the isolates in the present study exhibited host preferences across different states of India. Therefore, in order to protect vulnerable small ruminants from poxviral infections, it is recommended to take into consideration a homologous vaccination strategy.

Abstract 7291: Detection of a truncated form of multidrug resistance protein 1 (MRP1) in plasma sEVs derived from cancer patients

Abstract Multidrug resistance protein 1 (MRP1/ABCC1) is an ATP dependent transmembrane efflux pump that confers to drug resistance. Overexpression of MRP1 has been observed in both pancreatic ductal adenocarcinoma (PDAC) and breast cancer tissues. Numerous proteomics studies have revealed the presence of MRP1 in small extracellular vesicles (sEVs) released from cancer cells. Cancer-derived sEVs are known to be released into the circulation, thus becoming attractive candidates for non-invasive biomarker development. However, whether the MRP1 level in plasma sEVs is indicative of human cancer has not been evaluated. This study examined the MRP1 expression in plasma sEVs derived from patients with PDAC, breast and colon cancer, and age- and gender-matched healthy subjects. The patient plasma samples were obtained primarily from the NCI-sponsored Cooperative Human Tissue Network and Stephenson Cancer Center. Healthy plasma samples were provided by the Oklahoma Blood institute. Human pancreatic cancer cell lines PANC-1, MIA PaCa-2 and BxPC-3, and the pancreatic ductal cell line hTERT-HPNE were tested for MRP1 expression prior to examination of plasma samples. Cellular and plasma sEVs were isolated using the double filtration followed by polymer precipitation method. Western blot was performed to assess the expression level of MRP1 and proteomics was applied to confirm the detection of a truncated form of MRP1 in plasma sEVs. MRP1 expression was detected in the sEVs derived from all three pancreatic cancer cell lines but absent in the sEVs from the HPNE line. Overexpression of a truncated MRP1 protein was detected in plasma sEVs derived from patients with early stage (stage I-IIA) and late stage (III-IV) PDAC, compared with that from matched healthy subjects (n=17 for each group). Similar findings were evident in plasma sEVs from patients with breast cancer (n=7), while the results remained inconclusive in plasma sEVs from patients with colon cancer (n=7). Protein structure analysis indicated that the truncated form of MRP1 likely consists of the regions between the QCRL-1 motif and the C-terminus of the protein. Proteomic analysis detected the peptides derived from the C-terminus region, consistent with the structural analysis. Furthermore, the truncated form of MRP1 can only be detected using antibodies against the epitopes in the C-terminus and QCRL-1 region of MRP1 protein. In summary, we have detected a truncated form of MRP1 protein in plasma sEVs derived from cancer patients, and the level of its expression is significantly elevated in patients with PDAC and breast cancer. Citation Format: Kritisha Bhandari, Jeng Shi Kong, Chao Xu, Ajay Jain, Wei-Qun Ding. Detection of a truncated form of multidrug resistance protein 1 (MRP1) in plasma sEVs derived from cancer patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7291.

Abstract 4493: Protein structure inspired drug discovery

Abstract Introduction: Drug action is mediated by a small molecule therapeutic binding to a specific structural motif on a protein. As structure determines function, it follows that unique structural motifs are enriched for sites of unique function and high therapeutic target value. We hypothesized that protein structure constitutes high value primary information that can drive the discovery of novel therapeutic agents. Method: We developed a unique physics-based protein structure analysis platform scaled to run on a supercomputer, allowing us to consider dynamic protein flexibility and the influence of solvent upon protein structure, and to probe large protein libraries as a primary source of structure information that can support up-front structure-based screens. We developed and then probed a high resolution protein x-ray crystallographic library, created and curated by us. From a 60 million compound library, we conducted virtual screens for docking to identified sites. 8-day colony formation assays were conducted on a panel of 8 human breast, prostate, lung and colon cancer cell lines, as well as 8- and 14-day trilineage hematopoietic colony formation assays on human cord blood stem cells. Findings: From the first 180 deposited protein structures, we screened for unique protein surface structure. Structures were deemed unique if they were not otherwise known to be associated with any particular functional roles and were not the binding site of known therapeutics. Further selection included those that were clefts and possessed physical characteristics compatible with binding small chemicals whose properties have been linked to effective therapeutics. For each of 8 sites on 6 different proteins, a suite of analytics probed docking solutions from the compound library, generating a ranked list of 100 compounds for each site. Based on factors inclusive of availability and low potential for toxicity, compounds were acquired and used in in-parallel selection and de-selection functional assays. Cancer cell growth inhibition was a positive selection criterion, with additional ranking based on greater potency and broader efficacy. Bone marrow toxicity is limiting for most drugs, and inhibition of bone marrow stem cell growth was as a deselection criterion. Multiple compounds clustered around 2 sites on 2 different proteins. One compound, Dxr2-017, exhibited very high relative efficacy against colon and breast cancer cells. Evaluation of Dxr2-017 in the NCI-60 panel corroborated these findings, and showed even higher efficacy against melanoma. We demonstrated that Dxr2-017 inhibited melanoma growth with low nanomolar efficacy, while concentrations of over 2300-fold higher had only limited inhibitory effects on bone marrow stem cells. Conclusions: This study provides proof-of-principle that protein structure constitutes high value primary information that can support identification of novel therapeutics. This approach is widely applicable and expandable. Citation Format: Fangfang Qiao, T. Andrew Binkowski, Wayne Anderson, Weining Chen, Gray Schiltz, Karl Scheidt, Amarnath Natarajan, Raymond Bergan. Protein structure inspired drug discovery [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4493.

ATOMDANCE: Kernel-based denoising and choreographic analysis for protein dynamic comparison

Comparative methods in molecular evolution and structural biology rely heavily upon the site-wise analysis of DNA sequence and protein structure, both static forms of information. However, it is widely accepted that protein function results from nanoscale nonrandom machine-like motions induced by evolutionarily conserved molecular interactions. Comparisons of molecular dynamics (MD) simulations conducted between homologous sites representative of different functional or mutational states can potentially identify local effects on binding interaction and protein evolution. In addition, comparisons of different (i.e., nonhomologous) sites within MD simulations could be employed to identify functional shifts in local time-coordinated dynamics indicative of logic gating within proteins. However, comparative MD analysis is challenged by the large fraction of protein motion caused by random thermal noise in the surrounding solvent. Therefore, properly denoised MD comparisons could reveal functional sites involving these machine-like dynamics with good accuracy. Here, we introduce ATOMDANCE, a user-interfaced suite of comparative machine learning-based denoising tools designed for identifying functional sites and the patterns of coordinated motion they can create within MD simulations. ATOMDANCE-maxDemon4.0 employs Gaussian kernel functions to compute site-wise maximum mean discrepancy between learned features of motion, thereby assessing denoised differences in the nonrandom motions between functional or evolutionary states (e.g., ligand bound versus unbound, wild-type versus mutant). ATOMDANCE-maxDemon4.0 also employs maximum mean discrepancy to analyze potential random amino acid replacements allowing for a site-wise test of neutral versus nonneutral evolution on the divergence of dynamic function in protein homologs. Finally, ATOMDANCE-Choreograph2.0 employs mixed-model analysis of variance and graph network to detect regions where time-synchronized shifts in dynamics occur. Here, we demonstrate ATOMDANCE’s utility for identifying key sites involved in dynamic responses during functional binding interactions involving DNA, small-molecule drugs, and virus-host recognition, as well as understanding shifts in global and local site coordination occurring during allosteric activation of a pathogenic protease.

Investigation of porcine circovirus type 2 and porcine circovirus type 3 infections based on dual TaqMan fluorescent quantitative PCR method and genetic evolutionary analysis of these two viruses.

Porcine circovirus type 2 (PCV2) is the pathogen of Porcine Circovirus Associated Diseases. Porcine circovirus type 3 (PCV3) is a novel porcine circovirus associated with porcine dermatitis and nephropathy syndrome (PDNS) and reproductive failure. PCV2 is clearly pathogenic, while the pathogenicity of PCV3 remains controversial, so it is crucial to monitor the prevalence of PCV2 and PCV3 in healthy and diseased pigs to investigate the effects of PCV3 and PCV2 on the health status of pigs. Here, we developed a PCV2 and PCV3 dual TaqMan quantitative PCR (qPCR) method to test samples from healthy and diseased pigs, to clarify the differences in the positive rates and viral copy numbers of PCV2 and PCV3, and to analyze the genetic evolution and molecular characterization of the viral genomes obtained with sequence alignment and phylogenetic analysis, homology and structural analysis of Cap proteins, and selection pressure analysis. We successfully established a dual TaqMan qPCR method for PCV2 and PCV3 with good repeatability, specificity and sensitivity. In total, 1,385 samples from 15 Chinese provinces were tested with the established qPCR. The total positive rates were 37.47% for PCV3 and 57.95% for PCV2, and the coinfection rate for was 25.49%. The positive rates of PCV3 and PCV2 in 372 healthy pigs were 15.05 and 69.89%, respectively, and the coinfection rate was 12.90%. The positive rates of PCV3 and PCV2 in 246 diseased pigs were 55.69 and 83.33%, respectively, and the coinfection rate was 47.97%. Eighteen PCV3 genomes and 64 PCV2 genomes were identified, including nine each of the PCV3a-1 and PCV3b genotypes, eight of PCV2a, 16 of PCV2b, and 40 of PCV2d. The amino acid identity within the PCV3 Cap proteins was 94.00-100.0%, whereas the PCV2 Cap proteins showed an identity of 81.30-100.0%. PCV3 Cap was most variable at amino acid sites 24, 27, 77, 104 and 150, whereas PCV2 Cap had 10-13 unique sites of variation between genotypes. These results clarify the prevalence and variations of PCV2 and PCV3 in healthy and diseased pigs, which will provide a basis for the prevention and control of the two viral infections.

Genome-Wide Identification and Drought Stress Response Pattern of the NF-Y Gene Family in Cymbidium sinense.

Cymbidium sinense, a type of orchid plant, is more drought-resistant and ornamental than other terrestrial orchids. Research has shown that many members of the NUCLEAR FACTOR Y (NF-Y) transcription factor family are responsive to plant growth, development, and abiotic stress. However, the mechanism of the NF-Y gene family's response to abiotic stress in orchids has not yet been reported. In this study, phylogenetic analysis allowed for 27 CsNF-Y genes to be identified (5 CsNF-YAs, 9 CsNF-YBs, and 13 CsNF-YC subunits), and the CsNF-Ys were homologous to those in Arabidopsis and Oryza. Protein structure analysis revealed that different subfamilies contained different motifs, but all of them contained Motif 2. Secondary and tertiary protein structure analysis indicated that the CsNF-YB and CsNF-YC subfamilies had a high content of alpha helix structures. Cis-element analysis showed that elements related to drought stress were mainly concentrated in the CsNF-YB and CsNF-YC subfamilies, with CsNF-YB3 and CsNF-YC12 having the highest content. The results of a transcriptome analysis showed that there was a trend of downregulation of almost all CsNF-Ys in leaves under drought stress, while in roots, most members of the CsNF-YB subfamily showed a trend of upregulation. Additionally, seven genes were selected for real-time reverse transcription quantitative PCR (qRT-PCR) experiments. The results were generally consistent with those of the transcriptome analysis. The regulatory roles of CsNF-YB 1, 2, and 4 were particularly evident in the roots. The findings of our study may make a great contribution to the understanding of the role of CsNF-Ys in stress-related metabolic processes.

Unraveling the genetic variations underlying virulence disparities among SARS-CoV-2 strains across global regions: insights from Pakistan

Over the course of the COVID-19 pandemic, several SARS-CoV-2 variants have emerged that may exhibit different etiological effects such as enhanced transmissibility and infectivity. However, genetic variations that reduce virulence and deteriorate viral fitness have not yet been thoroughly investigated. The present study sought to evaluate the effects of viral genetic makeup on COVID-19 epidemiology in Pakistan, where the infectivity and mortality rate was comparatively lower than other countries during the first pandemic wave. For this purpose, we focused on the comparative analyses of 7096 amino-acid long polyprotein pp1ab. Comparative sequence analysis of 203 SARS-CoV-2 genomes, sampled from Pakistan during the first wave of the pandemic revealed 179 amino acid substitutions in pp1ab. Within this set, 38 substitutions were identified within the Nsp3 region of the pp1ab polyprotein. Structural and biophysical analysis of proteins revealed that amino acid variations within Nsp3’s macrodomains induced conformational changes and modified protein-ligand interactions, consequently diminishing the virulence and fitness of SARS-CoV-2. Additionally, the epistatic effects resulting from evolutionary substitutions in SARS-CoV-2 proteins may have unnoticed implications for reducing disease burden. In light of these findings, further characterization of such deleterious SARS-CoV-2 mutations will not only aid in identifying potential therapeutic targets but will also provide a roadmap for maintaining vigilance against the genetic variability of diverse SARS-CoV-2 strains circulating globally. Furthermore, these insights empower us to more effectively manage and respond to potential viral-based pandemic outbreaks of a similar nature in the future.

Bacterial hypothetical proteins may be of functional interest

Genomic analysis is part of the daily routine for many microbiology researchers. These analyses frequently unveil genes that encode proteins with uncertain functions, and for many bacterial species, these unknown genes constitute a significant proportion of their genomic coding sequences. Because these genes do not have defined functions, they are often overlooked in analyses. Experimentally determining the function of a gene can be challenging; however, ongoing advancements in bioinformatics tools, especially in protein structural analysis, are making it progressively easier to assign functions to hypothetical sequences. Leveraging various complementary tools and automated pipelines for annotating hypothetical sequences could ultimately enhance our comprehension of microbial functions and provide direction for new laboratory experiments.

Functional characterization of HNF4A gene variants identify promoter and cell line specific transactivation effects.

Hepatocyte nuclear factor-4 alpha (HNF-4A) regulates genes with roles in glucose metabolism and β-cell development. Although pathogenic HNF4A variants are commonly associated with maturity-onset diabetes of the young (MODY1; HNF4A-MODY), rare phenotypes also include hyperinsulinemic hypoglycemia, renal Fanconi syndrome and liver disease. While the association of rare functionally damaging HNF1A variants with HNF1A-MODY and type 2 diabetes is well established owing to robust functional assays, the impact of HNF4A variants on HNF-4A transactivation in tissues including the liver and kidney is less known, due to lack of similar assays. Our aim was to investigate the functional effects of seven HNF4A variants, located in the HNF-4A DNA binding domain and associated with different clinical phenotypes, by various functional assays and cell lines (transactivation, DNA binding, protein expression, nuclear localization) and in silico protein structure analyses. Variants R85W, S87N and R89W demonstrated reduced DNA binding to the consensus HNF-4A binding elements in the HNF1A promoter (35, 13 and 9%, respectively) and the G6PC promoter (R85W ~10%). While reduced transactivation on the G6PC promoter in HepG2 cells was shown for S87N (33%), R89W (65%) and R136W (35%), increased transactivation by R85W and R85Q was confirmed using several combinations of target promoters and cell lines. R89W showed reduced nuclear levels. In silico analyses supported variant induced structural impact. Our study indicates that cell line specific functional investigations are important to better understand HNF4A-MODY genotype-phenotype correlations, as our data supports ACMG/AMP interpretations of loss-of-function variants and propose assay-specific HNF4A control variants for future functional investigations.

Insights into the Structure-Function Relationship of GH70 GtfB α-Glucanotransferases from the Crystal Structure and Molecular Dynamic Simulation of a Newly Characterized Limosilactobacillus reuteri N1 GtfB Enzyme.

α-Glucanotransferases of the CAZy family GH70 convert starch-derived donors to industrially important α-glucans. Here, we describe characteristics of a novel GtfB-type 4,6-α-glucanotransferase of high enzyme activity (60.8 U mg-1) from Limosilactobacillus reuteri N1 (LrN1 GtfB), which produces surprisingly large quantities of soluble protein in heterologous expression (173 mg pure protein per L of culture) and synthesizes the reuteran-like α-glucan with (α1 → 6) linkages in linear chains and branch points. Protein structural analysis of LrN1 GtfB revealed the potential crucial residues at subsites -2∼+2, particularly H265, Y214, and R302, in the active center as well as previously unidentified surface binding sites. Furthermore, molecular dynamic simulations have provided unprecedented insights into linkage specificity hallmarks of the enzyme. Therefore, LrN1 GtfB represents a potent enzymatic tool for starch conversion, and this study promotes our knowledge on the structure-function relationship of GH70 GtfB α-glucanotransferases, which might facilitate the production of tailored α-glucans by enzyme engineering in future.

Genome-wide identification and expression analysis of the MADS gene family in sweet orange (Citrus sinensis) infested with pathogenic bacteria.

The risk of pathogenic bacterial invasion in plantations has increased dramatically due to high environmental climate change and has seriously affected sweet orange fruit quality. MADS genes allow plants to develop increased resistance, but functional genes for resistance associated with pathogen invasion have rarely been reported. MADS gene expression profiles were analyzed in sweet orange leaves and fruits infested with Lecanicillium psalliotae and Penicillium digitatum, respectively. Eighty-two MADS genes were identified from the sweet orange genome, and they were classified into five prime subfamilies concerning the Arabidopsis MADS gene family, of which the MIKC subfamily could be subdivided into 13 minor subfamilies. Protein structure analysis showed that more than 93% of the MADS protein sequences of the same subfamily between sweet orange and Arabidopsis were very similar in tertiary structure, with only CsMADS8 and AG showing significant differences. The variability of MADS genes protein structures between sweet orange and Arabidopsis subgroups was less than the variabilities of protein structures within species. Chromosomal localization and covariance analysis showed that these genes were unevenly distributed on nine chromosomes, with the most genes on chromosome 9 and the least on chromosome 2, with 36 and two, respectively. Four pairs of tandem and 28 fragmented duplicated genes in the 82 MADS gene sequences were found in sweet oranges. GO (Gene Ontology) functional enrichment and expression pattern analysis showed that the functional gene CsMADS46 was strongly downregulated of sweet orange in response to biotic stress adversity. It is also the first report that plants' MADS genes are involved in the biotic stress responses of sweet oranges. For the first time, L. psalliotae was experimentally confirmed to be the causal agent of sweet orange leaf spot disease, which provides a reference for the research and control of pathogenic L. psalliotae.

Advances in Membrane Mimetic Systems for Manipulation and Analysis of Membrane Proteins: Detergents, Polymers, Lipids and Scaffolds.

Extracting membrane proteins from the hydrophobic environment of the biological membrane, in a physiologically relevant and stable state, suitable for downstream analysis remains a challenge. The traditional route to membrane protein extraction has been to use detergents and the last 15 years or so have seen a veritable explosion in the development of novel detergents with improved properties, making them more suitable for individual proteins and specific applications. There have also been significant advances in the development of encapsulation of membrane proteins in lipid based nanodiscs, either directly from the native membrane using polymers allowing effective capture of the protein and protein-associated membrane lipids, or via reconstitution of detergent extracted and purified protein into nanodiscs of defined lipid composition. All of these advances have been successfully applied to the study of membrane proteins via a range of techniques and there have been some spectacular membrane protein structures solved. In addition, the first detailed structural and biophysical analyses of membrane proteins retained within a biological membrane have been reported. Here we summarise and review the recent advances with respect to these new agents and systems for membrane protein extraction, reconstitution and analysis.

Detection of driver mutations and genomic signatures in endometrial cancers using artificial intelligence algorithms.

Analyzed endometrial cancer (EC) genomes have allowed for the identification of molecular signatures, which enable the classification, and sometimes prognostication, of these cancers. Artificial intelligence algorithms have facilitated the partitioning of mutations into driver and passenger based on a variety of parameters, including gene function and frequency of mutation. Here, we undertook an evaluation of EC cancer genomes deposited on the Catalogue of Somatic Mutations in Cancers (COSMIC), with the goal to classify all mutations as either driver or passenger. Our analysis showed that approximately 2.5% of all mutations are driver and cause cellular transformation and immortalization. We also characterized nucleotide level mutation signatures, gross chromosomal re-arrangements, and gene expression profiles. We observed that endometrial cancers show distinct nucleotide substitution and chromosomal re-arrangement signatures compared to other cancers. We also identified high expression levels of the CLDN18 claudin gene, which is involved in growth, survival, metastasis and proliferation. We then used in silico protein structure analysis to examine the effect of certain previously uncharacterized driver mutations on protein structure. We found that certain mutations in CTNNB1 and TP53 increase protein stability, which may contribute to cellular transformation. While our analysis retrieved previously classified mutations and genomic alterations, which is to be expected, this study also identified new signatures. Additionally, we show that artificial intelligence algorithms can be effectively leveraged to accurately predict key drivers of cancer. This analysis will expand our understanding of ECs and improve the molecular toolbox for classification, diagnosis, or potential treatment of these cancers.