Cancers (Basel). 2024 Oct 29;16(21):3641. doi: 10.3390/cancers16213641.

ABSTRACT

Background: Non-Small Cell Lung Cancer (NSCLC) remains a challenging disease to manage with effectiveness. Early detection and precise monitoring are crucial for improving patient outcomes. Circulating tumor DNA (ctDNA) offers a non-invasive cancer detection and monitoring method. Emerging biomarkers, such as ctDNA methylation, have shown promise in enhancing diagnostic accuracy and prognostic assessment in NSCLC. In this review, we examined the current evidence regarding ctDNA methylation's role in NSCLC detection through a systematic review of the existing literature and meta-analysis. Methods: We systematically searched PubMed, Medline, Embase, and Web of Science databases up to 26 June 2024 for studies on the role of ctDNA methylation analysis in NSCLC patients. We included studies from 2010 to 2024 on NSCLC patients. We excluded case reports, non-English articles, studies on cell lines or artificial samples, those without cfDNA detection, prognostic studies, and studies with non-extractable data or mixed cancer types. Funnel plots were visually examined for potential publication bias, with a p value < 0.05 indicating bias. Meta-analysis was conducted using R packages (meta, forestplot, and mada). Combined sensitivity, specificity, positive likelihood ratio (LR+), negative likelihood ratio (LR-), positive and negative predictive values, diagnostic odds ratio (DOR), and 95% confidence intervals (95% CI) were calculated. A summary receiver operating characteristic curve (SROC) and area under the curve (AUC) with related Standard Error (SE) were used to evaluate the overall diagnostic performance. Additionally, RASSF1A, APC, SOX17, SEPT9, and RARβ2 were analyzed, since their methylation was assessed in two or more studies. Results: From 38 candidate papers, we finally identified 12 studies, including 472 NSCLC patients. The pooled sensitivity was 0.62 (0.47-0.77) and the specificity was 0.90 (0.85-0.94). The diagnostic odds ratio was 15.6 (95% CI 9.36-26.09) and the area under the curve was 0.249 (SE = 0.138). The positive and negative predictive values were 5.38 (95% CI 3.89-7.44) and 0.34 (95% CI 0.22-0.54), respectively. For single genes, the specificity reached 0.83~0.96, except for RARβ2, but the sensitivity was relatively low for each gene. Significant heterogeneity across the included studies, the potential publication bias for specificity (p = 0.0231), and the need to validate the clinical utility of ctDNA methylation for monitoring treatment response and predicting outcomes in NSCLC patients represent the main limitations of this study. Conclusions: These results provide evidence of the significant potential of ctDNA methylation as a valuable biomarker for improving the diagnosis of NSCLC, advocating for its integration into clinical practice to enhance patient management.

PMID:39518079 | DOI:10.3390/cancers16213641

Healthcare (Basel). 2024 Oct 30;12(21):2159. doi: 10.3390/healthcare12212159.

ABSTRACT

BACKGROUND: Mental stress plagued type II diabetes (T2DM) patients. The psychological and emotional issues related to diabetes and its effects include depression, anxiety, poor diet, and hypoglycemia fear.

AIM: Compare the impact of diabetes on depression and anxiety in Egyptian and Saudi diabetics.

METHODS: The diabetes, gastroenterology, and hepatology sections of University of Ha'il Clinic, KSA, and the Theodor Bilharz Research Institute, Egypt, conducted this retrospective study. Everyone gave informed consent before participating. Interviews with male and female outpatients and inpatients were conducted from June 2021 to December 2022. The self-administered validated Generalized Anxiety Disorder-7 (GAD-7) and the Patient Health Questionnaire-9 (PHQ-9) scale measured sociodemographic characteristics and symptoms of depression and anxiety.

RESULTS: In patients with diabetes, the prevalence of depression was higher in KSA [34.8%] than in Egypt [18%], while anxiety was higher in Egypt [40%] than in KSA [29.1%]. Most depressed patients were 31-55 years old (61.2%) from KSA and 97.8% (41-55 years old) from Egypt. Female anxiety was 70.7% in KSA and 51.0% in Egypt, with no significant difference. The duration of diabetes in depressed patients was 5-10 years ([46.9%, Saudis] vs. [57.8%, Egyptians]), while anxious patients (5-10 years [39.0%, Saudis] vs. >20 years [65.0%, Egyptians]) were mainly type-2. Most depressive patients had an HbA1c (59.2%) from 7-10% (Saudis) and 77.8% [>10% Egyptians] compared to anxiety patients (46.3%) and 48.0% [>10% Egyptians]. Depressed and anxious patients from both nations had higher glucose, triglycerides, and cholesterol levels. Saudis and Egyptians with obesity had higher rates of sadness (75.5% vs. 68.9%) and anxiety (82.9% vs. 69.0%). Treatment adherence and serum glucose monitoring were not significantly different from depression in diabetes individuals in both ethnicities.

CONCLUSIONS: Anxiety was more common among Egyptian patients because of overcrowding, working whole days to fulfill life requirements, and the unavailability of health insurance to all citizens. Meanwhile, in KSA, obesity, unhealthy food, and less exercise reflect the high percentage of depression among patients with diabetes. The detection of depression and anxiety in the context of DM should be critical for the physical health and quality of life of Saudi and Egyptian diabetics. Further investigation is warranted to encompass anxiety and depression within the scope of future research.

PMID:39517371 | DOI:10.3390/healthcare12212159

Foods. 2024 Oct 26;13(21):3411. doi: 10.3390/foods13213411.

ABSTRACT

Functional amyloids (protein nanofibrils, PNF) synthesized from plant sources exhibit unique physicochemical and nanomechanical properties that could improve food texture. While environmental factors affecting PNFs are well-known, scientific evidence on how cells (focus on the oral cavity) respond to them under physiological conditions is lacking. Self-assembled PNFs synthesized from fava bean whole protein isolate show a strong pH- and solvent-dependent morphology and elasticity modification measured by atomic force microscopy (AFM). After incubation of PNFs with an oral mechanosensitive model cell line at pH 7.3, difference in cell-surface roughness without significant changes in the overall cell elasticity were measured. The role of cell membrane composition on supported lipid bilayers was also tested, showing an increase in membrane elasticity with increasing fibril concentration and the possible impact of annular phospholipids in binding. Genetic responses of membrane proteins involved in texture and fat perception were detected at the mRNA level by RT-qPCR assay and both mechano- and chemosensing proteins displayed responses highlighting an interface dependent interaction. The outcomes of this study provide a basis for understanding the changing physicochemical properties of PNFs and their effect on flavor perception by altering mouthfeel and fat properties. This knowledge is important in the development of plant-based texture enhancers for sensory-appealing foods that require consumer acceptance and further promote healthy diets.

PMID:39517195 | DOI:10.3390/foods13213411

Commun Biol. 2024 Nov 8;7(1):1469. doi: 10.1038/s42003-024-07142-0.

ABSTRACT

Although primarily studied in relation to photorespiration, serine metabolism in chloroplasts may play a key role in plant CO2 fertilization responses by linking CO2 assimilation with growth. Here, we show that the phosphorylated serine pathway is part of a 'photosynthetic C1 pathway' and demonstrate its high activity in foliage of a C3 tree where it rapidly integrates photosynthesis and C1 metabolism contributing to new biomass via methyl transfer reactions, imparting a large natural 13C-depleted signature. Using 13CO2-labelling, we show that leaf serine, the S-methyl group of leaf methionine, pectin methyl esters, and the associated methanol released during cell wall expansion during growth, are directly produced from photosynthetically-linked C1 metabolism, within minutes of light exposure. We speculate that the photosynthetic C1 pathway is highly conserved across the photosynthetic tree of life, is responsible for synthesis of the greenhouse gas methane, and may have evolved with oxygenic photosynthesis by providing a mechanism of directly linking carbon and ammonia assimilation with growth. Although the rise in atmospheric CO2 inhibits major metabolic pathways like photorespiration, our results suggest that the photosynthetic C1 pathway may accelerate and represents a missing link between enhanced photosynthesis and plant growth rates during CO2 fertilization under a changing climate.

PMID:39516667 | DOI:10.1038/s42003-024-07142-0

Nat Cell Biol. 2024 Nov 8. doi: 10.1038/s41556-024-01546-0. Online ahead of print.

ABSTRACT

As tissues develop, cells divide and differentiate concurrently. Conflicting evidence shows that cell division is either dispensable or required for formation of cell types. Here, to determine the role of cell division in differentiation, we arrested the cell cycle in zebrafish embryos using two independent approaches and profiled them at single-cell resolution. We show that cell division is dispensable for differentiation of all embryonic tissues from early gastrulation to the end of segmentation. However, arresting cell division does slow down differentiation in some cell types, and it induces global stress responses. While differentiation is robust to blocking cell division, the proportions of cells across cell states are not, but show evidence of partial compensation. This work clarifies our understanding of the role of cell division in development and showcases the utility of combining embryo-wide perturbations with single-cell RNA sequencing to uncover the role of common biological processes across multiple tissues.

PMID:39516639 | DOI:10.1038/s41556-024-01546-0

Sci Rep. 2024 Nov 9;14(1):27318. doi: 10.1038/s41598-024-78648-0.

ABSTRACT

Accessible mammography datasets and innovative machine learning techniques are at the forefront of computer-aided breast cancer diagnosis. However, the opacity surrounding private datasets and the unclear methodology behind the selection of subset images from publicly available databases for model training and testing, coupled with the arbitrary incompleteness or inaccessibility of code, markedly intensifies the obstacles in replicating and validating the model's efficacy. These challenges, in turn, erect barriers for subsequent researchers striving to learn and advance this field. To address these limitations, we provide a pilot codebase covering the entire process from image preprocessing to model development and evaluation pipeline, utilizing the publicly available Curated Breast Imaging Subset of Digital Database for Screening Mammography (CBIS-DDSM) mass subset, including both full images and regions of interests (ROIs). We have identified that increasing the input size could improve the detection accuracy of malignant cases within each set of models. Collectively, our efforts hold promise in accelerating global software development for breast cancer diagnosis by leveraging our codebase and structure, while also integrating other advancements in the field.

PMID:39516557 | DOI:10.1038/s41598-024-78648-0

Sci Rep. 2024 Nov 8;14(1):27209. doi: 10.1038/s41598-024-78313-6.

ABSTRACT

Oncolytic virotherapy has shown efficacy in various animal models and a few human cancers. However, there are still significant limitations for the implementation of these therapies. One such limitation is the emergence of cellular resistances, which may appear rapidly considering the high genetic heterogeneity of most tumors. We previously showed that cellular resistance to an oncolytic virus can be mediated by the chronic activation of innate immunity. Here, we explored the existence of additional resistance mechanisms in murine colon cancer-derived cells. For this purpose, we isolated two cellular clones that were resistant to the oncolytic virus VSV-D51. While one of the clones showed a strong resistance profile associated with increased cytokine-mediated antiviral responses, the other clone showed a lower level of resistance that involves cytoskeletal reorganization, signaling by small GTPases, and cell structural changes. These results demonstrate the capacity of tumor cells to deploy heterogeneous mechanisms of resistance to oncolytic viruses.

PMID:39516525 | DOI:10.1038/s41598-024-78313-6

EMBO J. 2024 Nov 8. doi: 10.1038/s44318-024-00297-w. Online ahead of print.

ABSTRACT

Maturation of human mitochondrial tRNA is essential for cellular energy production, yet the underlying mechanisms remain only partially understood. Here, we present several cryo-EM structures of the mitochondrial RNase Z complex (ELAC2/SDR5C1/TRMT10C) bound to different maturation states of mitochondrial tRNAHis, showing the molecular basis for tRNA-substrate selection and catalysis. Our structural insights provide a molecular rationale for the 5'-to-3' tRNA processing order in mitochondria, the 3'-CCA antideterminant effect, and the basis for sequence-independent recognition of mitochondrial tRNA substrates. Furthermore, our study links mutations in ELAC2 to clinically relevant mitochondrial diseases, offering a deeper understanding of the molecular defects contributing to these conditions.

PMID:39516281 | DOI:10.1038/s44318-024-00297-w

Nat Commun. 2024 Nov 8;15(1):9561. doi: 10.1038/s41467-024-53989-6.

ABSTRACT

Evidence from homogeneous liquid or flat-plate cultures indicates that biochemical cues are the primary modes of bacterial interaction with their microenvironment. However, these systems fail to capture the effect of physical confinement on bacteria in their natural habitats. Bacterial niches like the pores of soil, mucus, and infected tissues are disordered microenvironments with material properties defined by their internal pore sizes and shear moduli. Here, we use three-dimensional matrices that match the viscoelastic properties of gut mucus to test how altering the physical properties of their microenvironment influences the growth of bacteria under confinement. We find that low aspect ratio (spherical) bacteria form compact, spherical colonies under confinement while high aspect ratio (rod-shaped) bacteria push their progenies further outwards to create elongated colonies with a higher surface area, enabling increased access to nutrients. As a result, the population growth of high aspect ratio bacteria is, under the tested conditions, more robust to increased physical confinement compared to that of low aspect ratio bacteria. Thus, our experimental evidence supports that environmental physical constraints can play a selective role in bacterial growth based on cell shape.

PMID:39516204 | DOI:10.1038/s41467-024-53989-6

Virol Sin. 2024 Nov 6:S1995-820X(24)00172-X. doi: 10.1016/j.virs.2024.11.001. Online ahead of print.

ABSTRACT

Human adenoviruses (HAdVs) are highly contagious pathogens with various genotypes implicated in acute respiratory disease (ARD) and linked to mortality, especially in immunosuppressed patients, young children, and military recruits. Currently, no vaccines or specific drugs are approved for clinical use. The hosts of adenoviruses are strictly species-specific, which strongly limits the development of vaccines and drugs against HAdVs. In this study, immunocompetent BALB/c mice were challenged with different doses of human adenovirus type 5 (HAdV-5) via tail intravenous injection (i.v.). All mice challenged with a high dose of HAdV-5 (3.2×1010 TCID50/kg) died within 3 to 5 days, while those receiving a low dose of HAdV-5 (8×109 or 4×109 TCID50/kg) survived. Interestingly, among the mice receiving a medium dose of HAdV-5 (1.6×1010 TCID50/kg), 60% (n = 3/5) of male mice died, while all female mice survived. This suggests that male mice may be more susceptible to HAdV-5 infection than female mice, consistent with clinical findings in children. HAdV-5 DNA was mainly distributed in the liver, followed by the spleen and lungs. Pathological changes were observed in the lungs, liver, and spleen, with severity increasing in correlation with the virus challenge dosage. Transcriptome and qPCR analyses of the liver indicated that the down-regulated expression of the H2-Aa, H2-Ea-ps, CD74, and H2-Eb1 genes in male mice, as well as the AHR gene in female mice, may contribute to the observed higher mortality rates in male mice. Therefore, this effective, feasible, and cost-efficient mouse model could serve as a candidate for evaluating HAdV vaccines and anti-adenovirus therapeutics.

PMID:39515524 | DOI:10.1016/j.virs.2024.11.001

Cell Rep Methods. 2024 Nov 5:100899. doi: 10.1016/j.crmeth.2024.100899. Online ahead of print.

ABSTRACT

Identifying predictive biomarkers of patient outcomes from high-throughput microbiome data is of high interest, while existing computational methods do not satisfactorily account for complex survival endpoints, longitudinal samples, and taxa-specific sequencing biases. We present FLORAL, an open-source tool to perform scalable log-ratio lasso regression and microbial feature selection for continuous, binary, time-to-event, and competing risk outcomes, with compatibility for longitudinal microbiome data as time-dependent covariates. The proposed method adapts the augmented Lagrangian algorithm for a zero-sum constraint optimization problem while enabling a two-stage screening process for enhanced false-positive control. In extensive simulation and real-data analyses, FLORAL achieved consistently better false-positive control compared to other lasso-based approaches and better sensitivity over popular differential abundance testing methods for datasets with smaller sample sizes. In a survival analysis of allogeneic hematopoietic cell transplant recipients, FLORAL demonstrated considerable improvement in microbial feature selection by utilizing longitudinal microbiome data over solely using baseline microbiome data.

PMID:39515336 | DOI:10.1016/j.crmeth.2024.100899

Cell Rep Methods. 2024 Nov 6:100900. doi: 10.1016/j.crmeth.2024.100900. Online ahead of print.

ABSTRACT

In diseases such as cancer, the design of new therapeutic strategies requires extensive, costly, and unfortunately sometimes deadly testing to reveal life threatening off-target effects. We hypothesized that the disease specificity of targets can be systematically learned for all genes by jointly evaluating complementary molecular measurements of healthy tissues using a hierarchical Bayesian modeling approach. Our method, BayesTS, integrates protein and gene expression evidence and includes tunable parameters to moderate tissue essentiality. Applied to all protein coding genes, BayesTS outperforms alternative strategies to define therapeutic targets and nominates previously unknown targets while allowing for incorporation of new types of modalities. To expand target repertoires, we show that extension of BayesTS to splicing antigens and combinatorial target pairs results in more specific targets for therapy. We expect that BayesTS will facilitate improved target prioritization for oncology drug development, ultimately leading to the discovery of more effective and safer treatments.

PMID:39515334 | DOI:10.1016/j.crmeth.2024.100900

Cell Rep Methods. 2024 Nov 5:100896. doi: 10.1016/j.crmeth.2024.100896. Online ahead of print.

ABSTRACT

Protein natural diversity offers a vast sequence space for protein engineering, and deep learning enables its detection from metagenomes/proteomes without prior assumptions. DeepMetagenome, a Python-based method, explores protein diversity through modules for training and analyzing sequence datasets. The deep learning model includes Embedding, Conv1D, LSTM, and Dense layers, with sequence feature analysis for data cleaning. Applied to metallothioneins from a database of over 146 million coding features, DeepMetagenome identified over 500 high-confidence metallothionein sequences, outperforming DIAMOND and CNN-based models. It showed stable performance compared to a Transformer-based model over 25 epochs. Among 23 synthesized sequences, 20 exhibited metal resistance. The tool also successfully explored the diversity of three additional protein families and is freely available on GitHub with detailed instructions.

PMID:39515333 | DOI:10.1016/j.crmeth.2024.100896

Cell Rep Methods. 2024 Nov 1:100886. doi: 10.1016/j.crmeth.2024.100886. Online ahead of print.

ABSTRACT

Spatial transcriptomics is a groundbreaking technology, enabling simultaneous profiling of gene expression and spatial orientation within biological tissues. Yet when analyzing spatial transcriptomics data, effective integration of expression and spatial information poses considerable analytical challenges. Although many methods have been developed to address this issue, many are platform specific and lack the general applicability to analyze diverse datasets. In this article, we propose a method called the weighted ensemble method for spatial transcriptomics (WEST) that utilizes ensemble techniques to improve the performance and robustness of spatial transcriptomics data analytics. We compare the performance of WEST with six methods on both synthetic and real-world datasets. WEST represents a significant advance in detecting spatial domains, offering improved accuracy and flexibility compared to existing methods, making it a valuable tool for spatial transcriptomics data analytics.

PMID:39515332 | DOI:10.1016/j.crmeth.2024.100886

J Proteome Res. 2024 Nov 8. doi: 10.1021/acs.jproteome.4c00776. Online ahead of print.

ABSTRACT

The Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify at least one isoform of every protein-coding gene and (2) to make proteomics an integral part of multiomics studies of human health and disease. The past year has seen major transitions for the HPP. neXtProt was retired as the official HPP knowledge base, UniProtKB became the reference proteome knowledge base, and Ensembl-GENCODE provides the reference protein target list. A function evidence FE1-5 scoring system has been developed for functional annotation of proteins, parallel to the PE1-5 UniProtKB/neXtProt scheme for evidence of protein expression. This report includes updates from neXtProt (version 2023-09) and UniProtKB release 2024_04, with protein expression detected (PE1) for 18138 of the 19411 GENCODE protein-coding genes (93%). The number of non-PE1 proteins ("missing proteins") is now 1273. The transition to GENCODE is a net reduction of 367 proteins (19,411 PE1-5 instead of 19,778 PE1-4 last year in neXtProt). We include reports from the Biology and Disease-driven HPP, the Human Protein Atlas, and the HPP Grand Challenge Project. We expect the new Functional Evidence FE1-5 scheme to energize the Grand Challenge Project for functional annotation of human proteins throughout the global proteomics community, including π-HuB in China.

PMID:39514846 | DOI:10.1021/acs.jproteome.4c00776

Sci Adv. 2024 Nov 8;10(45):eadq9580. doi: 10.1126/sciadv.adq9580. Epub 2024 Nov 8.

ABSTRACT

Coronavirus-infected cells contain double-membrane vesicles (DMVs) that are key for viral RNA replication and transcription, perforated by hexameric pores connecting the vesicular lumen to the cytoplasm. How pores form and traverse two membranes, and how DMVs organize RNA synthesis, is unknown. Using structure prediction and functional assays, we show that the nonstructural viral membrane protein nsp4 is the key pore organizer, spanning the double membrane and forming most of the pore lining. Nsp4 interacts with nsp3 on the cytoplasmic side and with the viral replicase inside the DMV. Newly synthesized mRNAs exit the DMV into the cytoplasm, passing through a narrow ring of conserved nsp4 residues. Steric constraints imposed by the ring predict that modified nucleobases block mRNA transit, resulting in broad-spectrum anticoronaviral activity.

PMID:39514670 | DOI:10.1126/sciadv.adq9580

Anal Chem. 2024 Nov 8. doi: 10.1021/acs.analchem.4c04091. Online ahead of print.

ABSTRACT

Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization process to ensure broad applicability to many applications. As part of the Human Proteome Organization Proteomics Standards Initiative (PSI), we have developed a standardized format for encoding spectral libraries, called mzSpecLib (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly encodes metadata about the library entries using the extensible PSI-MS controlled vocabulary and can be encoded in and converted between different serialization formats. We have also developed a standardized data model and serialization for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF). It is defined as a separate standard, since it may be used for other applications besides spectral libraries. The mzSpecLib and mzPAF standards are compatible with existing PSI standards such as ProForma 2.0 and the Universal Spectrum Identifier. The mzSpecLib and mzPAF standards have been primarily defined for peptides in proteomics applications with basic small molecule support. They could be extended in the future to other fields that need to encode spectral libraries for nonpeptidic analytes.

PMID:39514576 | DOI:10.1021/acs.analchem.4c04091

Front Physiol. 2024 Oct 23;15:1473125. doi: 10.3389/fphys.2024.1473125. eCollection 2024.

ABSTRACT

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature.

PMID:39507514 | PMC:PMC11537925 | DOI:10.3389/fphys.2024.1473125

ACS Catal. 2024 Oct 14;14(21):15976-15987. doi: 10.1021/acscatal.4c04815. eCollection 2024 Nov 1.

ABSTRACT

Halohydrin dehalogenase HheG and its homologues are remarkable enzymes for the efficient ring opening of sterically demanding internal epoxides using a variety of nucleophiles. The enantioselectivity of the respective wild-type enzymes, however, is usually insufficient for application and frequently requires improvement by protein engineering. We herein demonstrate that the highly flexible N-terminal loop of HheG, comprising residues 39 to 47, has a tremendous impact on the activity as well as enantioselectivity of this enzyme in the ring opening of structurally diverse epoxide substrates. Thus, highly active and enantioselective HheG variants could be accessed through targeted engineering of this loop. In this regard, variant M45F displayed almost 10-fold higher specific activity than wild type in the azidolysis of cyclohexene oxide, yielding the corresponding product (1S,2S)-2-azidocyclohexan-1-ol in 96%eeP (in comparison to 49%eeP for HheG wild type). Moreover, this variant was also improved regarding activity and enantioselectivity in the ring opening of cyclohexene oxide with other nucleophiles, demonstrating even inverted enantioselectivity with cyanide and cyanate. In contrast, a complete loop deletion yielded an inactive enzyme. Concomitant computational analyses of HheG M45F in comparison to wild type enzyme revealed that mutation M45F promotes the productive binding of cyclohexene oxide and azide in the active site by establishing noncovalent C-H ··π interactions between epoxide and F45. These interactions further position one of the two carbon atoms of the epoxide ring closer to the azide, resulting in higher enantioselectivity. Additionally, stable and enantioselective cross-linked enzyme crystals of HheG M45F were successfully generated after combination with mutation D114C. Overall, our study highlights that a highly flexible loop in HheG governs the enzyme's activity and selectivity in epoxide ring opening and should thus be considered in future protein engineering campaigns of HheG.

PMID:39507489 | PMC:PMC11536340 | DOI:10.1021/acscatal.4c04815

Ann Transl Med. 2024 Oct 20;12(5):93. doi: 10.21037/atm-24-25. Epub 2024 Aug 14.

ABSTRACT

Laparoscopic colon surgery is performed frequently in the clinical setting for a multitude of reasons including cancer, infection, and autoimmune disease. As a result, extensive research has been conducted in relation to clinical outcomes after surgery, but more recently, in relation to the impact of surgery and other patient factors on physiologic homeostasis including the host microbiome. Despite this, experimental surgical models for laparoscopic colon surgery are scarce in the literature with most studies utilizing rodents. While rodent studies provide valuable insights into basic mechanistic processes, the translation of novel therapeutic approaches to clinical practice often requires the use of large animal models. In exploring the intricate systems biology linking surgery and medicine, sophisticated models such as nonhuman primates (NHPs) play a pivotal role. By closely resembling human anatomical, physiological, and behavioral characteristics, NHPs facilitate the development and refinement of complex surgical techniques and peri-operative practices. Furthermore, they enable longitudinal studies that comprehensively assess both immediate and long-term outcomes. The availability and utilization of multiple robust models enhance the validity of surgical research, leading to more successful translation to human clinical practice. Here we describe our technique for performing a laparoscopic sigmoid colectomy with a primary anastomosis in an NHP. The entire procedure was well tolerated without significant ventilation or hemodynamic issue. To our knowledge, this represents the first laparoscopic sigmoid colectomy with primary anastomosis performed in an NHP. Furthermore, this demonstrates the feasibility of the technique and provides a relevant, preclinical model for the study of surgical colon disease. Although the surgical colectomy model in NHPs closely resembles the clinical scenario, it is crucial to recognize that a 'model' inherently comes with limitations. The intended use of any model should be carefully evaluated concerning the target patient population with the consideration of potential disparities in anatomy, physiology, environmental factors, and disease to properly interpret results. This model provides an opportunity to study mechanisms, from a systems biology perspective, underlying both innovative surgical treatments and their effects on diseases such as colon cancer, as well as benign conditions like inflammatory bowel disease, diverticulitis, and anastomotic leak, offering high predictive value.

PMID:39507443 | PMC:PMC11534753 | DOI:10.21037/atm-24-25