Serum bile acid and unsaturated fatty acid profiles of non-alcoholic fatty liver disease in type 2 diabetic patients

BACKGROUND The understanding of bile acid(BA)and unsaturated fatty acid(UFA)profiles,as well as their dysregulation,remains elusive in individuals with type 2 diabetes mellitus(T2DM)coexisting with non-alcoholic fatty liver disease(NAFLD).Investigating these metabolites could offer valuable insights into the pathophy-siology of NAFLD in T2DM.AIM To identify potential metabolite biomarkers capable of distinguishing between NAFLD and T2DM.METHODS A training model was developed involving 399 participants,comprising 113 healthy controls(HCs),134 individuals with T2DM without NAFLD,and 152 individuals with T2DM and NAFLD.External validation encompassed 172 participants.NAFLD patients were divided based on liver fibrosis scores.The analytical approach employed univariate testing,orthogonal partial least squares-discriminant analysis,logistic regression,receiver operating characteristic curve analysis,and decision curve analysis to pinpoint and assess the diagnostic value of serum biomarkers.RESULTS Compared to HCs,both T2DM and NAFLD groups exhibited diminished levels of specific BAs.In UFAs,particular acids exhibited a positive correlation with NAFLD risk in T2DM,while theω-6:ω-3 UFA ratio demonstrated a negative correlation.Levels ofα-linolenic acid andγ-linolenic acid were linked to significant liver fibrosis in NAFLD.The validation cohort substantiated the predictive efficacy of these biomarkers for assessing NAFLD risk in T2DM patients.CONCLUSION This study underscores the connection between altered BA and UFA profiles and the presence of NAFLD in individuals with T2DM,proposing their potential as biomarkers in the pathogenesis of NAFLD.

iCEMIGE: Integration of CEll-morphometrics, MIcrobiome, and GEne biomarker signatures for risk stratification in breast cancers

BACKGROUND The development of precision medicine is essential for personalized treatment and improved clinical outcome,whereas biomarkers are critical for the success of precision therapies.AIM To investigate whether iCEMIGE(integration of CEll-morphometrics,MIcro-biome,and GEne biomarker signatures)improves risk stratification of breast cancer(BC)patients.METHODS We used our recently developed machine learning technique to identify cellular morphometric biomarkers(CMBs)from the whole histological slide images in The Cancer Genome Atlas(TCGA)breast cancer(TCGA-BRCA)cohort.Multivariate Cox regression was used to assess whether cell-morphometrics prognosis score(CMPS)and our previously reported 12-gene expression prognosis score(GEPS)and 15-microbe abundance prognosis score(MAPS)were independent prognostic factors.iCEMIGE was built upon the sparse representation learning technique.The iCEMIGE scoring model performance was measured by the area under the receiver operating characteristic curve compared to CMPS,GEPS,or MAPS alone.Nomogram models were created to predict overall survival(OS)and progress-free survival(PFS)rates at 5-and 10-year in the TCGA-BRCA cohort.RESULTS We identified 39 CMBs that were used to create a CMPS system in BCs.CMPS,GEPS,and MAPS were found to be significantly independently associated with OS.We then established an iCEMIGE scoring system for risk stratification of BC patients.The iGEMIGE score has a significant prognostic value for OS and PFS independent of clinical factors(age,stage,and estrogen and progesterone receptor status)and PAM50-based molecular subtype.Importantly,the iCEMIGE score significantly increased the power to predict OS and PFS compared to CMPS,GEPS,or MAPS alone.CONCLUSION Our study demonstrates a novel and generic artificial intelligence framework for multimodal data integration toward improving prognosis risk stratification of BC patients,which can be extended to other types of cancer.

Perspective on oligomeric products from lignin depolymerization:their generation,identification,and further valorization

The present contribution emphasizes the formation of oligomeric products in various depolymerization approaches of lignin,namely reductive catalytic fractionation,oxidative catalytic fractionation,and pyrolysis.Three possible routes to form such oligomers in these depolymerization processes are summarized and compared from various studies conducted on model compounds.Next,the main identification techniques for characterizing oligomeric products are highlighted.Particular focus is given to 2D-HSQC-NMR,GPC,Maldi-TOF-MS and FT-ICR-MS,which represent the state-of-art characterization of lignin.Special attention was paid to the transferability of these techniques for depolymerized oligomeric lignin.Finally,both the existing and expected potential lignin valorization routes are discussed for these oligomers,and technical hurdles and recommendations are provided in an attempt to catalyze the development of new discoveries and enabling technologies.

Scalable and automated CRISPR-based strain engineering using droplet microfluidics

We present a droplet-based microfluidic system that enables CRISPR-based gene editing and high-throughput screening on a chip.The microfluidic device contains a 10x10 element array,and each element contains sets of electrodes for two electric field-actuated operations:electrowetting for merging droplets to mix reagents and electroporation for transformation.This device can perform up to 100 genetic modification reactions in parallel,providing a scalable platform for generating the large number of engineered strains required for the combinatorial optimization of genetic pathways and predictable bioengineering.We demonstrate the system's capabilities through the CRISPR-based engineering of two test cases:(1)disruption of the function of the enzyme galactokinase(galK)in£coli and(2)targeted engineering of the glutamine synthetase gene(glnA)and the blue-pigment synthetase gene(bpsA)to improve indigoidine production in£coli.

A FAIR-compliant parts catalogue for genome engineering and expression control in Saccharomyces cerevisiae

The synthetic biology toolkit for baker’s yeast,Saccharomyces cerevisiae,includes extensive genome engineering toolkits and parts repositories.However,with the increasing complexity of engineering tasks and versatile applications of this model eukaryote,there is a continued interest to expand and diversify the rational engineering capabilities in this chassis by FAIR(findable,accessible,interoperable,and reproducible)compliance.In this study,we designed and characterised 41 synthetic guide RNA sequences to expand the CRISPR-based genome engineering capabilities for easy and efficient replacement of genomically encoded elements.Moreover,we characterize in high temporal resolution 20 native promoters and 18 terminators using fluorescein and LUDOX CL-X as references for GFP expression and OD600 measurements,respectively.Additionally,all data and reported analysis is provided in a publicly accessible jupyter notebook providing a tool for researchers with low-coding skills to further explore the generated data as well as a template for researchers to write their own scripts.We expect the data,parts,and databases associated with this study to support a FAIR-compliant resource for further advancing the engineering of yeasts.

Residential energy transition and chronic respiratory diseases

Obtaining clean energy is of prime importance for planetary health and sustainable development.We aimed to assess the association between residential energy transition and the risk of chronic respiratory diseases.Using data from the Global Health Observatory and Global Burden of Diseases,Injuries,and Risk Factors Study,we delineated the spatial distribution and temporal trends of the population using clean fuels for cooking at a global scale.In the China Health and Retirement Longitudinal Study,we performed rigorous and well-structured multistage analyses incorporating both cross-sectional and prospective data analyses to examine the associations between solid fuel use,residential energy transition,duration of solid fuel use,and the risk of chronic respiratory diseases.Despite great progress,huge disparities in access to clean energy persist globally.Residential energy transition was associated with a lower risk of chronic respiratory diseases.In the period of 2011–2013,compared with persistent solid fuel users,both participants who switched from solid to clean fuels(adjusted risk ratio[RR]0.78,95%confidence interval[CI]0.62–0.98)and persistent clean fuel users(adjusted RR 0.71,95%CI 0.57–0.89)had significantly lower risk of chronic respiratory diseases(p<0.001 for trend).Consistent associations were observed in the period of 2011–2015 and 2011–2018.Household energy transition from solid to clean fuels could reduce the risk of chronic respiratory diseases.This is a valuable lesson for policy-makers and the general public to accelerate energy switching to alleviate the burden of chronic respiratory diseases and achieve health benefits,particularly in low-and middle-income countries.

Thirdhand smoke: Genotoxicity and carcinogenic potential

Thirdhand smoke (THS), the residual tobacco smoke remaining in the environment after tobacco has been smoked, represents a hidden and underestimated public health hazard. Evidence supports its widespread presence in indoor environments. Exposure to secondhand smoke (SHS), a precursor of THS, has been well documented as a risk factor for human cancers, especially lung cancer. However, the concept of THS as a distinct entity that poses health risks for small children has developed only recently and the associations of THS with cancer risk and other chronic diseases are poorly understood due to limited numbers of studies to date. In this perspective, we mainly summarize all published studies on the genotoxicity and carcinogenic potential of THS exposure. These studies begin to fill the knowledge gap in our understanding of cancer risk of THS. Accumulating data from existing and future studies will help reduce the tobacco-related cancer incidence through changes in lifestyle and tobacco control policies.

Plant Biosystems Design Research Roadmap 1.0

Human life intimately depends on plants for food,biomaterials,health,energy,and a sustainable environment.Various plants have been genetically improved mostly through breeding,along with limited modification via genetic engineering,yet they are still not able to meet the ever-increasing needs,in terms of both quantity and quality,resulting from the rapid increase in world population and expected standards of living.A step change that may address these challenges would be to expand the potential of plants using biosystems design approaches.This represents a shift in plant science research from relatively simple trial-and-error approaches to innovative strategies based on predictive models of biological systems.Plant biosystems design seeks to accelerate plant genetic improvement using genome editing and genetic circuit engineering or create novel plant systems through de novo synthesis of plant genomes.From this perspective,we present a comprehensive roadmap of plant biosystems design covering theories,principles,and technical methods,along with potential applications in basic and applied plant biology research.We highlight current challenges,future opportunities,and research priorities,along with a framework for international collaboration,towards rapid advancement of this emerging interdisciplinary area of research.Finally,we discuss the importance of social responsibility in utilizing plant biosystems design and suggest strategies for improving public perception,trust,and acceptance.

Carbene chemistry for unnatural biosynthesis

Previously,chemists working in synthesis were jealous of biologists since the enzymes found in nature usually exhibited great catalytic properties(e.g.,high catalytic efficiency,excellent selectivity such as substrate selectivity,regioselectivity and stereoselectivity).However,biological systems lack many counterparts of reactions widely used in chemical synthesis.

Overcoming the challenges of cancer drug resistance through bacterial-mediated therapy

Despite tremendous efforts to fight cancer,it remains a major public health problem and a leading cause of death worldwide.With increased knowledge of cancer pathways and improved technological platforms,precision therapeutics that specifically target aberrant cancer pathways have improved patient outcomes.Nevertheless,a primary cause of unsuccessful cancer therapy remains cancer drug resistance.In this review,we summarize the broad classes of resistance to cancer therapy,particularly pharmacokinetics,the tumor microenvironment,and drug resistance mechanisms.Furthermore,we describe how bacterial-mediated cancer therapy,a bygone mode of treatment,has been revitalized by synthetic biology and is uniquely suited to address the primary resistance mechanisms that confound traditional therapies.Through genetic engineering,we discuss how bacteria can be potent anticancer agents given their tumor targeting potential,anti-tumor activity,safety,and coordinated delivery of anti-cancer drugs.

Characterizing cellular mechanical phenotypes with mechanonode-pore sensing

The mechanical properties of cells change with their differentiation,chronological age,and malignant progression.Consequently,these properties may be useful label-free biomarkers of various functional or clinically relevant cell states.Here,we demonstrate mechano-node-pore sensing(mechano-NPS),a multi-parametric single-cell-analysis method that utilizes a four-terminal measurement of the current across a microfluidic channel to quantify simultaneously cell diameter,resistance to compressive deformation,transverse deformation under constant strain,and recovery time after deformation.We define a new parameter,the whole-cell deformability index(wCDI),which provides a quantitative mechanical metric of the resistance to compressive deformation that can be used to discriminate among different cell types.The wCDI and the transverse deformation under constant strain show malignant MCF-7 and A549 cell lines are mechanically distinct from non-malignant,MCF-10A and BEAS-2B cell lines,and distinguishes between cells treated or untreated with cytoskeleton-perturbing small molecules.We categorize cell recovery time,ΔT_(r),as instantaneous(ΔTr~0 ms),transient(ΔT_(r)≤40 ms),or prolonged(ΔT_(r)>40 ms),and show that the composition of recovery types,which is a consequence of changes in cytoskeletal organization,correlates with cellular transformation.Through the wCDI and cell-recovery time,mechano-NPS discriminates between sub-lineages of normal primary human mammary epithelial cells with accuracy comparable to flow cytometry,but without antibody labeling.Mechano-NPS identifies mechanical phenotypes that distinguishes lineage,chronological age,and stage of malignant progression in human epithelial cells.

MEP pathway products allosterically promote monomerization of deoxy-D-xylulose-5-phosphate synthase to feedback-regulate their supply

Isoprenoids are a very large and diverse family of metabolites required by all living organisms.All isoprenoids derive fromthe double-bond isomers isopentenyl diphosphate(IPP)and dimethylallyl diphosphate(DMAPP),which are produced by the methylerythritol 4-phosphate(MEP)pathway in bacteria and plant plastids.It has been reported that IPP and DMAPP feedback-regulate the activity of deoxyxylulose 5-phosphate synthase(DXS),a dimeric enzyme that catalyzes the main flux-controlling step of the MEP pathway.Here we provide experimental insights intotheunderlyingmechanism.Isothermal titration calorimetry and dynamic light scattering approaches showed that IPP and DMAPP can allosterically bind to DXS in vitro,causing a size shift.In silico ligand binding site analysis and docking calculations identified a potential allosteric site in the contact region between the two monomers of the active DXS dimer.Modulation of IPP and DMAPP contents in vivo followed by immunoblot analyses confirmed that high IPP/DMAPP levels resulted in monomerization and eventual aggregation of the enzyme in bacterial and plant cells.Loss of the enzymatically active dimeric conformation allows a fast and reversible reduction of DXS activity in response to a sudden increase or decrease in IPP/DMAPP supply,whereas aggregation and subsequent removal of monomers that would otherwise be available for dimerization appears to be a more drastic response in the case of persistent IPP/DMAPP overabundance(e.g.,by a blockage in their conversion to downstream isoprenoids).Our results represent an important step toward understanding the regulation of the MEP pathway and rational design of biotechnological endeavors aimed at increasing isoprenoid contents in microbial and plant systems.