Single-cell ionic current phenotyping elucidates non-canonical features and predictive potential of cardiomyocytes during automated drug experiments.

All new drugs must go through preclinical screening tests to determine their proarrhythmic potential. While these assays effectively filter out dangerous drugs, they are too conservative, often misclassifying safe compounds as proarrhythmic. In this study, we attempt to address this shortcoming with a novel, medium-throughput drug-screening approach: we use an automated patch-clamp system to acquire optimized voltage clamp (VC) and action potential (AP) data from human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) at several drug concentrations (baseline, 3×, 10× and 20× the effective free plasma concentrations). With our novel method, we show correlations between INa block and upstroke slowing after treatment with flecainide or quinine. Additionally, after quinine treatment, we identify significant reductions in current during voltage steps designed to isolate If and IKs. However, we do not detect any IKr block by either drug, and upon further investigation, do not see any IKr present in the iPSC-CMs when prepared for automated patch experiments (i.e. in suspension) - this is in contrast to similar experiments we have conducted with these cells using the manual patch setup. In this study, we: (1) present a proof-of-concept demonstration of a single-cell medium-throughput drug study, and (2) characterize the non-canonical electrophysiology of iPSC-CMs when prepared for experiments in a medium-throughput setting. KEY POINTS: Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) offer potential as an in vitro model to study the proarrhythmic potential of drugs, but insights from these cells are often limited by the low throughput of manual patch-clamp. In this study, we use a medium-throughput automated patch-clamp system to acquire action potential (AP) and complex voltage clamp (VC) data from single iPSC-CMs at multiple drug concentrations. A correlation between AP upstroke and INa transients was identified and drug-induced changes in ionic currents found. We also characterize the substantially altered physiology of iPSC-CMs when patched in an automated system, suggesting the need to investigate differences between manual and automated patch experiments.

Integrated Biofilm Modification and Transcriptional Analysis for Improving Fengycin Production in Bacillus amyloliquefaciens.

Although fengycin exhibits broad-spectrum antifungal properties, its application is hindered due to its low biosynthesis level and the co-existence of iturin A and surfactin in Bacillus amyloliquefaciens HM618, a probiotic strain. In this study, transcriptome analysis and gene editing were used to explore the potential mechanisms regulating fengycin production in B. amyloliquefaciens. The fengycin level of B. amyloliquefacien HM-3 (∆itu-ΔsrfAA) was 88.41 mg/L after simultaneously inhibiting the biosyntheses of iturin A and surfactin. The knockout of gene eps associated with biofilm formation significantly increased the fengycin level of the strain HM618, whereas the fengycin level decreased 32.05% after knocking out sinI, a regulator of biofilm formation. Transcriptome analysis revealed that the differentially expressed genes, involved in pathways of amino acid and fatty acid syntheses, were significantly down-regulated in the recombinant strains, which is likely associated with a decrease of fengycin production. The knockout of gene comQXPA and subsequent transcriptome analysis revealed that the ComQXPA quorum sensing system played a positive regulatory role in fengycin production. Through targeted genetic modifications and fermentation optimization, the fengycin production of the engineered strain HM-12 (∆itu-ΔsrfAA-ΔyvbJ) in a 5-L fermenter reached 1.172 g/L, a 12.26-fold increase compared to the fengycin level in the strain HM-3 (∆itu-ΔsrfAA) in the Erlenmeyer flask. Taken together, these results reveal the underlying metabolic mechanisms associated with fengycin synthesis and provide a potential strategy for improving fengycin production in B. amyloliquefaciens.

The molecular subtypes of autoimmune diseases.

Autoimmune diseases (ADs) are characterized by their complexity and a wide range of clinical differences. Despite patients presenting with similar symptoms and disease patterns, their reactions to treatments may vary. The current approach of personalized medicine, which relies on molecular data, is seen as an effective method to address the variability in these diseases. This review examined the pathologic classification of ADs, such as multiple sclerosis and lupus nephritis, over time. Acknowledging the limitations inherent in pathologic classification, the focus shifted to molecular classification to achieve a deeper insight into disease heterogeneity. The study outlined the established methods and findings from the molecular classification of ADs, categorizing systemic lupus erythematosus (SLE) into four subtypes, inflammatory bowel disease (IBD) into two, rheumatoid arthritis (RA) into three, and multiple sclerosis (MS) into a single subtype. It was observed that the high inflammation subtype of IBD, the RA inflammation subtype, and the MS "inflammation & EGF" subtype share similarities. These subtypes all display a consistent pattern of inflammation that is primarily driven by the activation of the JAK-STAT pathway, with the effective drugs being those that target this signaling pathway. Additionally, by identifying markers that are uniquely associated with the various subtypes within the same disease, the study was able to describe the differences between subtypes in detail. The findings are expected to contribute to the development of personalized treatment plans for patients and establish a strong basis for tailored approaches to treating autoimmune diseases.

A review of disease risk prediction methods and applications in the omics era.

Risk prediction and disease prevention are the innovative care challenges of the 21st century. Apart from freeing the individual from the pain of disease, it will lead to low medical costs for society. Until very recently, risk assessments have ushered in a new era with the emergence of omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and so on, which potentially advance the ability of biomarkers to aid prediction models. While risk prediction has achieved great success, there are still some challenges and limitations. We reviewed the general process of omics-based disease risk model construction and the applications in four typical diseases. Meanwhile, we highlighted the problems in current studies and explored the potential opportunities and challenges for future clinical practice.

Single-cell ionic current phenotyping explains stem cell-derived cardiomyocyte action potential morphology.

Human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) are a promising tool to study arrhythmia-related factors, but the variability of action potential (AP) recordings from these cells limits their use as an in vitro model. In this study, we use recently published brief (10 s), dynamic voltage-clamp (VC) data to provide mechanistic insights into the ionic currents contributing to AP heterogeneity; we call this approach rapid ionic current phenotyping (RICP). Features of this VC data were correlated to AP recordings from the same cells, and we used computational models to generate mechanistic insights into cellular heterogeneity. This analysis uncovered several interesting links between AP morphology and ionic current density: both L-type calcium and sodium currents contribute to upstroke velocity, rapid delayed rectifier K+ current is the main determinant of the maximal diastolic potential, and an outward current in the activation range of slow delayed rectifier K+ is the main determinant of AP duration. Our analysis also identified an outward current in several cells at 6 mV that is not reproduced by iPSC-CM mathematical models but contributes to determining AP duration. RICP can be used to explain how cell-to-cell variability in ionic currents gives rise to AP heterogeneity. Because of its brief duration (10 s) and ease of data interpretation, we recommend the use of RICP for single-cell patch-clamp experiments that include the acquisition of APs.NEW & NOTEWORTHY We present rapid ionic current phenotyping (RICP), a current quantification approach based on an optimized voltage-clamp protocol. The method captures a rich snapshot of the ionic current dynamics, providing quantitative information about multiple currents (e.g., ICa,L, IKr) in the same cell. The protocol helped to identify key ionic determinants of cellular action potential heterogeneity in iPSC-CMs. This included unexpected results, such as the critical role of IKr in establishing the maximum diastolic potential.

Enhancement of polymyxin B1 production by an artificial microbial consortium of Paenibacillus polymyxa and recombinant Corynebacterium glutamicum producing precursor amino acids.

Polymyxin B, produced by Paenibacillus polymyxa, is used as the last line of defense clinically. In this study, exogenous mixture of precursor amino acids increased the level and proportion of polymyxin B1 in the total of polymyxin B analogs of P. polymyxa CJX518-AC (PPAC) from 0.15 g/L and 61.8 % to 0.33 g/L and 79.9 %, respectively. The co-culture of strain PPAC and recombinant Corynebacterium glutamicum-leu01, which produces high levels of threonine, leucine, and isoleucine, increased polymyxin B1 production to 0.64 g/L. When strains PPAC and C. glu-leu01 simultaneously inoculated into an optimized medium with 20 g/L peptone, polymyxin B1 production was increased to 0.97 g/L. Furthermore, the polymyxin B1 production in the co-culture of strains PPAC and C. glu-leu01 increased to 2.21 g/L after optimized inoculation ratios and fermentation medium with 60 g/L peptone. This study provides a new strategy to improve polymyxin B1 production.

An Engineered Microbial Consortium Provides Precursors for Fengycin Production by Bacillus subtilis.

Fengycin has great potential for applications in biological control because of its biosafety and degradability. In this study, the addition of exogenous precursors increased fengycin production by Bacillus subtilis. Corynebacterium glutamicum was engineered to produce high levels of precursors (Thr, Pro, Val, and Ile) to promote the biosynthesis of fengycin. Furthermore, recombinant C. glutamicum and Yarrowia lipolytica providing amino acid and fatty acid precursors were co-cultured to improve fengycin production by B. subtilis in a three-strain artificial consortium, in which fengycin production was 2100 mg·L-1. In addition, fengycin production by the consortium in a 5 L bioreactor reached 3290 mg·L-1. Fengycin had a significant antifungal effect on Rhizoctonia solani, which illustrates its potential as a food preservative. Taken together, this work provides a new strategy for improving fengycin production by a microbial consortium and metabolic engineering.

Effects of genetic variation on the structure of RNA and protein.

Changes in the structure of RNA and protein, have an important impact on biological functions and are even important determinants of disease pathogenesis and treatment. Some genetic variations, including copy number variation, single nucleotide variation, and so on, can lead to changes in biological function and increased susceptibility to certain diseases by changing the structure of RNA or protein. With the development of structural biology and sequencing technology, a large amount of RNA and protein structure data and genetic variation data resources has emerged to be used to explain biological processes. Here, we reviewed the effects of genetic variation on the structure of RNAs and proteins, and investigated their impact on several diseases. An online resource (http://www.onethird-lab.com/gems/) to support convenient retrieval of common tools is also built. Finally, the challenges and future development of the effects of genetic variation on RNA and protein were discussed.

Prognostic value of DNA methylation subclassification, aneuploidy, and CDKN2A/B homozygous deletion in predicting clinical outcome of IDH mutant astrocytomas.

INTRODUCTION: IDH mutant astrocytoma grading, until recently, has been entirely based on morphology. The 5th edition of the Central Nervous System WHO introduces CDKN2A/B homozygous deletion as a biomarker of grade 4. We sought to investigate the prognostic impact of DNA methylation-derived molecular biomarkers for IDH mutant astrocytoma. METHODS: We analyzed 98 IDH mutant astrocytomas diagnosed at NYU Langone Health between 2014 and 2022. We reviewed DNA methylation subclass, CDKN2A/B homozygous deletion, and ploidy and correlated molecular biomarkers with histological grade, progression free (PFS), and overall (OS) survival. Findings were confirmed using two independent validation cohorts. RESULTS: There was no significant difference in OS or PFS when stratified by histologic WHO grade alone, copy number complexity, or extent of resection. OS was significantly different when patients were stratified either by CDKN2A/B homozygous deletion or by DNA methylation subclass (p-value=0.0286 and 0.0016, respectively). None of the molecular biomarkers were associated with significantly better progression free survival (PFS), although DNA methylation classification showed a trend (p-value= 0.0534). CONCLUSIONS: The current WHO recognized grading criteria for IDH mutant astrocytomas show limited prognostic value. Stratification based on DNA methylation shows superior prognostic value for OS.

Enhanced ability of toluene oxidation by controlling inversion degree of spinel composed of only Co, Mn.

Exploring the single relationship between the inversion degree of spinel and its catalytic performance is a great challenge, but has important significance for further structural design and application. A series of CoMn inverse spinels were prepared and the general formula [Formula: see text] was deduced through X-ray diffraction refinement to find a decreased inversion degree x as calcination temperature rose. Catalytic oxidation of toluene showed that higher inversion degree (S-300 with x ≈ 0.95) can reach larger conversion rate (90 % at about 250 °C for 400 ppm toluene) with greater reaction stability (140 h). Density Functional Theory (DFT) calculations on density of states indicated its metallic nature, and found that the strength of O-p and Transition metal-d orbitals at Fermi energy is positively correlated to the inversion degree, meaning stronger electron migration ability. Along with the adsorption calculation analysis that lattice oxygen species are proved to work dominantly (S-300 with lowest adsorption energy but highest performance), this work uncovered a theoretical insight into inverse spinel oxide, to provide the possibility of elevated oxidation ability through structural control.

Detection of pesticide residues on flexible and transparent fluorinated polyimide film based on surface-enhanced Raman spectroscopy technology.

BACKGROUND: Excessive pesticide residues will seriously endanger human health. The complexity and lag of the current popular analytical methods hinder the timeliness of food safety analysis. Surface-enhanced Raman scattering (SERS) was an ultra-sensitive vibration spectroscopy technology with the advantages of less time cost, non-destructive and semi-quantitative detection, which has attracted much attention in the rapid field detection of pesticide residue. It was clear that we need an efficient and convenient substrate for pesticide residue detection based on SRES technology, which needs to be portable, flexible, transparent and easy to detect irregular object surfaces. RESULTS: A novel SERS sensor was designed to detect single and multi-component pesticide residues on irregular fruit and vegetable surfaces by in-situ growth of silver nanoparticles on a flexible and transparent fluorinated polyimide (FPI) substrate. Among them, Ag NPs were synthesized by liquid phase reduction method (AgNO3-PVP and NaBH4). The results showed that the detection limit of 1-4 BDT was down to 10-10 mol L-1, the enhancement factor (EF) was up to 1.57 × 107, and relative standard deviation (RSD) was 7.49 %. By this method, tricyclazole solution at a concentration of 0.01 mg L-1 was still detectable by the FPI@Ag SERS substrate. The linear quantification was achieved in the range from 100 mg L-1 to 0.01 mg L-1. Two mixed pesticides, tricyclazole and imazalil, were also successfully distinguished. SIGNIFICANCE: This represents the formation of a flexible, foldable and transparent substrate for rapid on-site detection. Results can be obtained in <5 min by attaching the substrate to the substance to be tested. And the SERS substrate prepared with high sensitivity, stability, portable and convenient analysis, which provided new ideas for efficient and rapid household food safety detection.

Genome-wide identification of m6A-associated single nucleotide polymorphisms in complex diseases of nervous system.

N6-methyladenosine (m6A) is one of the most abundant chemical modifications on RNA and can affect the occurrence and development of diseases. Some studies have shown that the expressions of some m6A-related genes are significantly regulated by single nucleotide variants (SNV). However, the function of m6A-associated single nucleotide polymorphisms (m6A-SNP) remains unclear in multiple sclerosis (MS), Alzheimer's disease (AD) and Parkinson's disease (PD). Here, we identified the disease-associated m6A-SNPs by integrating genome-wide association study (GWAS) and m6A-SNPs from the RMVar database, and confirmed the relationship between these identified m6A-SNPs and their target genes in eQTL analysis and gene differential expression analysis. Finally, 26 genes corresponding to 20 m6A-SNPs with eQTL signals were identified and differentially expressed (P < 0.05) in MS, 15 genes corresponding to 12 m6A-SNPs (P < 1e-04) were differentially expressed in AD, and 27 PD-associated m6A-SNPs that regulated the expression of 31 genes were identified. There were 5 HLA genes with eQTL signals (HLA-DQB1, HLA-DRB1, HLA-DQA1, HLA-DQA2 and HLA-DQB1-AS1) to be detected in the three diseases. In summary, our study provided new insights into understanding the potential roles of these m6A-SNPs in disease pathogenesis as well as therapeutic target.

Epigenome-wide methylation haplotype association analysis identified HLA-DRB1, HLA-DRB5 and HLA-DQB1 as risk factors for rheumatoid arthritis.

The aim of this study was to compare nonrandom associations between physically adjacent single methylation polymorphism loci among rheumatoid arthritis (RA) and normal subjects for investigating RA-risk methylation haplotypes (meplotype). With 354 ACPA-positive RA patients and 335 normal controls selected from a case-control study based on Swedish population, we conducted the first RA epigenome-wide meplotype association study using our software EWAS2.0, mainly including (i) converted the ß value to methylation genotype (menotype) data, (ii) identified methylation disequilibrium (MD) block, (iii) calculated frequent of each meplotypes in MD block and performed case-control association test and (iv) screened for RA-risk meplotypes by odd ratio (OR) and p-values. Ultimately, 545 meplotypes on 334 MD blocks were identified significantly associated with RA (p-value < .05). These meplotypes were mapped to 329 candidate genes related to RA. Subsequently, combined with gene optimization, eight RA-risk meplotypes were identified on three risk genes: HLA-DRB1, HLA-DRB5 and HLA-DQB1. Our results reported the relationship between DNA methylation pattern on HLA-DQB1 and the risk of RA for the first time, demonstrating the co-demethylation of 'cg22984282' and 'cg13423887' on HLA-DQB1 gene (meplotype UU, p-value = 2.90E - 6, OR = 1.68, 95% CI = [1.35, 2.10]) may increase the risk of RA. Our results demonstrates the potential of methylation haplotype analysis to identify RA-related genes from a new perspective and its applicability to the study of other disease.

CCDC43 as a potential therapeutic target of Tian Yang Wan for the treatment of hepatocellular carcinoma by activating the hippo pathway.

Introduction: Hepatocellular carcinoma (HCC) prevalence is rising annually, but the existing treatment strategies are limited; therefore, it is crucial to explore new therapeutic approaches. Methods: Here, we investigate the potential anti-cancer mechanism of an herbal medicine called Tian Yang Wan (TYW) in the treatment of HCC. The relationship of CCDC43 with immunity and cell death was analyzed by bioinformatics. Confirming the tumor suppressor effect of TYW on HCC cells by proliferation, invasion, migration and apoptosis assays. Results: First, we analyzed by proteomics that CCDC43 expression was downregulated after TYW administration and promoted the hippo pathway. Then, a large sample's transcriptome study demonstrated that elevated CCDC43 expression was strongly correlated with clinical traits and a bad prognosis in HCC patients. Next, we observed through multiple advanced algorithms that CCDC43 is involved in a variety of oncology and immunology related pathways. Notably, we found higher tumor immune microenvironment with high CCDC43 expression. Furthermore, we demonstrated that CCDC43 is associated with immune checkpoints and found that it is a sensitive indicator of a large number of chemotherapeutic agents. Subsequently, we conducted experimental investigations to demonstrate the capacity of TYW to impede proliferation and migration, while inducing apoptosis in human HCC cell lines. Finally, we performed analysis of two cell death patterns which showed CCDC43 to be strongly correlated with multiple ferroptosis factors and cuproptosis factors. Discusion: In conclusion, our study comprehensively examined the prognostic, immunological, and therapeutic implications of CCDC43 in HCC, thereby elucidating the therapeutic mechanism of action in TYW.

Leak current, even with gigaohm seals, can cause misinterpretation of stem cell-derived cardiomyocyte action potential recordings.

AIMS: Human-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) have become an essential tool to study arrhythmia mechanisms. Much of the foundational work on these cells, as well as the computational models built from the resultant data, has overlooked the contribution of seal-leak current on the immature and heterogeneous phenotype that has come to define these cells. The aim of this study is to understand the effect of seal-leak current on recordings of action potential (AP) morphology. METHODS AND RESULTS: Action potentials were recorded in human iPSC-CMs using patch clamp and simulated using previously published mathematical models. Our in silico and in vitro studies demonstrate how seal-leak current depolarizes APs, substantially affecting their morphology, even with seal resistances (Rseal) above 1 GΩ. We show that compensation of this leak current is difficult due to challenges with obtaining accurate measures of Rseal during an experiment. Using simulation, we show that Rseal measures (i) change during an experiment, invalidating the use of pre-rupture values, and (ii) are polluted by the presence of transmembrane currents at every voltage. Finally, we posit that the background sodium current in baseline iPSC-CM models imitates the effects of seal-leak current and is increased to a level that masks the effects of seal-leak current on iPSC-CMs. CONCLUSION: Based on these findings, we make recommendations to improve iPSC-CM AP data acquisition, interpretation, and model-building. Taking these recommendations into account will improve our understanding of iPSC-CM physiology and the descriptive ability of models built from such data.

Rapid ionic current phenotyping (RICP) identifies mechanistic underpinnings of iPSC-CM AP heterogeneity.

As a renewable, easily accessible, human-derived in vitro model, human induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) are a promising tool for studying arrhythmia-related factors, including cardiotoxicity and congenital proarrhythmia risks. An oft-mentioned limitation of iPSC-CMs is the abundant cell-to-cell variability in recordings of their electrical activity. Here, we develop a new method, rapid ionic current phenotyping (RICP), that utilizes a short (10 s) voltage clamp protocol to quantify cell-to-cell heterogeneity in key ionic currents. We correlate these ionic current dynamics to action potential recordings from the same cells and produce mechanistic insights into cellular heterogeneity. We present evidence that the L-type calcium current is the main determinant of upstroke velocity, rapid delayed rectifier K+ current is the main determinant of the maximal diastolic potential, and an outward current in the excitable range of slow delayed rectifier K+ is the main determinant of action potential duration. We measure an unidentified outward current in several cells at 6 mV that is not recapitulated by iPSC-CM mathematical models but contributes to determining action potential duration. In this way, our study both quantifies cell-to-cell variability in membrane potential and ionic currents, and demonstrates how the ionic current variability gives rise to action potential heterogeneity. Based on these results, we argue that iPSC-CM heterogeneity should not be viewed simply as a problem to be solved but as a model system to understand the mechanistic underpinnings of cellular variability.

LESION MIMIC MUTANT 1 confers basal resistance to Sclerotinia sclerotiorum in rapeseed via a salicylic acid-dependent pathway.

Rapeseed (Brassica napus) is a major edible oilseed crop consumed worldwide. However, its yield is seriously affected by infection from the broad-spectrum non-obligate pathogen Sclerotinia sclerotiorum due to a lack of highly resistant germplasm. Here, we identified a Sclerotinia-resistant and light-dependent lesion mimic mutant from an ethyl methanesulfonate-mutagenized population of the rapeseed inbred Zhongshuang 11 (ZS11) named lesion mimic mutant 1 (lmm1). The phenotype of lmm1 is controlled by a single recessive gene, named LESION MIMIC MUTANT 1 (LMM1), which mapped onto chromosome C04 by bulked segregant analysis within a 2.71-Mb interval. Histochemical analysis indicated that H2O2 strongly accumulated and cell death occurred around the lesion mimic spots. Among 877 differentially expressed genes (DEGs) between ZS11 and lmm1 leaves, 188 DEGs were enriched in the defense response, including 95 DEGs involved in systemic acquired resistance, which is consistent with the higher salicylic acid levels in lmm1. Combining bulked segregant analysis and transcriptome analysis, we identified a significantly up-regulated gene, BnaC4.PR2, which encodes ß-1,3-glucanase, as the candidate gene for LMM1. Overexpression of BnaC4.PR2 may induce a reactive oxygen species burst to trigger partial cell death and systemic acquired resistance. Our study provides a new genetic resource for S. sclerotiorum resistance as well as new insights into disease resistance breeding in B. napus.

Climate warming negatively affects plant water-use efficiency in a seasonal hydroperiod wetland.

Climate warming has substantial influences on plant water-use efficiency (PWUE), which is defined as the ratio of plant CO2 uptake to water loss and is central to the cycles of carbon and water in ecosystems. However, it remains uncertain how does climate warming affect PWUE in wetland ecosystems, especially those with seasonally alternating water availability during the growing season. In this study, we used a continuous 10-year (2011-2020) eddy covariance (EC) dataset from a seasonal hydroperiod wetland coupled with a 15-year (2003-2017) satellite-based dataset (called PML-V2) and an in situ warming experiment to examine the climate warming impacts on wetland PWUE. The 10-year EC observational results revealed that rising temperatures had significant negative impacts on the interannual variations in wetland PWUE, and increased transpiration (Et) rather than changes in gross primary productivity (GPP) dominated these negative impacts. Furthermore, the 15-year satellite-based evidence confirmed that, in the study region, climate warming had significant negative consequences for the interannual variations in wetland PWUE by enhancing wetland Et. Lastly, at the leaf-scale, the light response curves of leaf photosynthesis, leaf Et, and leaf-scale PWUE indicated that wetland plants need to consume more water during the photosynthesis process under warmer conditions. These findings provide a fresh perspective on how climate warming influences carbon and water cycles in wetland ecosystems.

Enhancing fengycin production in the co-culture of Bacillus subtilis and Corynebacterium glutamicum by engineering proline transporter.

Fengycin possesses antifungal activity but has limited application due to its low yields. Amino acid precursors play a crucial role in fengycin synthesis. Herein, the overexpression of alanine, isoleucine, and threonine transporter-related genes in Bacillus subtilis increased fengycin production by 34.06%, 46.66%, and 7.83%, respectively. Particularly, fengycin production in B. subtilis reached 871.86 mg/L with the addition of 8.0 g/L exogenous proline after enhancing the expression of the proline transport-related gene opuE. To overcome the metabolic burden caused by excessive enhancement of gene expression for supplying precursors, B. subtilis and Corynebacterium glutamicum which produced proline, were co-cultured, which further improved fengycin production. Fengycin production in the co-culture of B. subtilis and C. glutamicum in shake flasks reached 1554.74 mg/L after optimizing the inoculation time and ratio. The fengycin level in the fed-batch co-culture was 2309.96 mg/L in a 5.0-L bioreactor. These findings provide a new strategy for improving fengycin production.

Dynamic changes of inulin utilization associated with longitudinal development of gut microbiota.

Inulin is a typical kind of fermentable polysaccharide and has emerged as a promising dietary supplement due to its multiple health-promoting effects. This study aimed to unveil the dynamic change pattern of inulin utilizability as a fermentation substrate during gut microbiota development and illuminate its potential association with gut microbiota in Chinese Jinhua native pig models via longitudinal analyses. Herein, fresh feces were collected at one week pre- and post-weaning as well as 3rd month post-weaning, respectively. Targeted metabolomics and in vitro simulated fermentation revealed increasing concentrations of fecal short-chain fatty acids (SCFAs) and elevating utilizability of inulin as a fermentation substrate. Microbiomic analyses demonstrated the conspicuous longitudinal alteration in gut microbial composition and a significant rise in microbial community diversity during gut microbiota development. Furthermore, gut microbial functional analyses showed a remarkable increase in the relative abundances of carbohydrate metabolism pathways, including pentose phosphate pathway, galactose metabolism pathway, butanoate metabolism pathway as well as fructose and mannose metabolism pathway. Notably, relative abundances of bacterial genera Bifidobacterium, Roseburia, Faecalibacterium and Enterococcus displayed significantly positive correlations with the production of microbial fermentation-derived SCFAs. Collectively, these findings offer novel insights into understanding inulin utilizability variations from the perspective of gut microbiota development.