A Computational Approach for Designing Synthetic Riboswitches for Next-Generation RNA Therapeutics.

Riboswitches are naturally occurring regulatory segments of RNA molecules that modulate gene expression in response to specific ligand binding. They serve as a molecular 'switch' that controls the RNA's structure and function, typically influencing the synthesis of proteins. Riboswitches are unique because they directly interact with metabolites without the need for proteins, making them attractive tools in synthetic biology and RNA-based therapeutics. In synthetic biology, riboswitches are harnessed to create biosensors and genetic circuits. Their ability to respond to specific molecular signals allows for the design of precise control mechanisms in genetic engineering. This specificity is particularly useful in therapeutic applications, where riboswitches can be synthetically designed to respond to disease-specific metabolites, thereby enabling targeted drug delivery or gene therapy. Advancements in designing synthetic riboswitches for RNA-based therapeutics hinge on sophisticated computational techniques, which are described in this chapter. The chapter concludes by underscoring the potential of computational strategies in revolutionizing the design and application of synthetic riboswitches, paving the way for advanced RNA-based therapeutic solutions.

Engineering artificial cross-species promoters with different transcriptional strengths.

As a fundamental tool in synthetic biology, promoters are pivotal in regulating gene expression, enabling precise genetic control and spurring innovation across diverse biotechnological applications. However, most advances in engineered genetic systems rely on host-specific regulation of the genetic portion. With the burgeoning diversity of synthetic biology chassis cells, there emerges a pressing necessity to broaden the universal promoter toolkit spectrum, ensuring adaptability across various microbial chassis cells for enhanced applicability and customization in the evolving landscape of synthetic biology. In this study, we analyzed and validated the primary structures of natural endogenous promoters from Escherichia coli, Bacillus subtilis, Corynebacterium glutamicum, Saccharomyces cerevisiae, and Pichia pastoris, and through strategic integration and rational modification of promoter motifs, we developed a series of cross-species promoters (Psh) with transcriptional activity in five strains (prokaryotic and eukaryotic). This series of cross species promoters can significantly expand the synthetic biology promoter toolkit while providing a foundation and inspiration for standardized development of universal components The combinatorial use of key elements from prokaryotic and eukaryotic promoters presented in this study represents a novel strategy that may offer new insights and methods for future advancements in promoter engineering.

BDNF-dependent nano-organization of Neogenin and the WAVE regulatory complex promotes actin remodeling in dendritic spines.

Synaptic structural plasticity, the expansion of dendritic spines in response to synaptic stimulation, is essential for experience-dependent plasticity and is driven by branched actin polymerization. The WAVE regulatory complex (WRC) is confined to nanodomains at the postsynaptic membrane where it catalyzes actin polymerization. As the netrin/RGM receptor Neogenin is a critical regulator of the WRC, its nanoscale organization may be an important determinant of WRC nanoarchitecture and function. Using super-resolution microscopy, we reveal that Neogenin is highly organized on the spine membrane at the nanoscale level. We show that Neogenin binding to the WRC promotes co-clustering into nanodomains in response to brain-derived neurotrophic factor (BDNF), indicating that nanoclustering occurs in response to synaptic stimulation. Disruption of Neogenin/WRC binding not only prevents BDNF-mediated actin remodeling but also inhibits BDNF-induced calcium signaling. We conclude that the assembly of Neogenin/WRC nanodomains is a prerequisite for BDNF-mediated structural and synaptic plasticity.

Quantitative mapping of proteasome interactomes and substrates using ProteasomeID.

Proteasomes are essential molecular machines responsible for the degradation of proteins in eukaryotic cells. Altered proteasome activity has been linked to neurodegeneration, auto-immune disorders and cancer. Despite the relevance for human disease and drug development, no method currently exists to monitor proteasome composition and interactions in vivo in animal models. To fill this gap, we developed a strategy based on tagging of proteasomes with promiscuous biotin ligases and generated a new mouse model enabling the quantification of proteasome interactions by mass spectrometry. We show that biotin ligases can be incorporated in fully assembled proteasomes without negative impact on their activity. We demonstrate the utility of our method by identifying novel proteasome-interacting proteins, charting interactomes across mouse organs, and showing that proximity-labeling enables the identification of both endogenous and small-molecule-induced proteasome substrates.

The G protein-coupled receptor ADGRG6 maintains mouse growth plate homeostasis through IHH Signaling.

The cartilage growth plate is essential for maintaining skeletal growth; however, the mechanisms governing postnatal growth plate homeostasis are still poorly understood. Using approaches of molecular mouse genetics and spatial transcriptomics applied to formalin-fixed, paraffin-embedded (FFPE) tissues, we show that ADGRG6/GPR126, a cartilage-enriched adhesion G protein-coupled receptor (GPCR), is essential for maintaining slow-cycling resting zone cells, appropriate chondrocyte proliferation and differentiation, and growth plate homeostasis in mice. Constitutive ablation of Adgrg6 in osteochondral progenitor cells with Col2a1Cre leads to a shortened resting zone, formation of cell clusters within the proliferative zone, and an elongated hypertrophic growth plate, marked by limited expression of PTHrP but increased IHH signaling throughout the growth plate. Attenuation of Smoothened (SMO)-dependent hedgehog signaling restored the Adgrg6 deficiency-induced expansion of hypertrophic chondrocytes, confirming that IHH signaling can promote chondrocyte hypertrophy in a PTHrP-independent manner. In contrast, postnatal ablation of Adgrg6 in mature chondrocytes with AcanCreERT2, induced after the formation of the resting zone, does not affect PTHrP expression but causes an overall reduction of growth plate thickness marked by increased cell death specifically in the resting zone cells and a general reduction of chondrocyte proliferation and differentiation. Spatial transcriptomics reveals that ADGRG6 is essential for maintaining chondrocyte homeostasis by regulating osteogenic and catabolic genes in all the zones of the postnatal growth plates, potentially through positive regulation of SOX9 expression. Our findings elucidate the essential role of a cartilage-enriched adhesion GPCR in regulating cell proliferation and hypertrophic differentiation by regulation of PTHrP/IHH signaling, maintenance of slow-cycle resting zone chondrocytes, and safeguarding chondrocyte homeostasis in postnatal mouse growth plates.

The cartilage growth plate is an essential structure for skeletal growth, however, the mechanisms that govern growth plate homeostasis are still poorly understood. In this study, we showed that an adhesion G protein-coupled receptor (GPCR) named ADGRG6 plays an essential role in maintaining the slow-cycling cells in the resting zone of the growth plate and directing appropriate proliferation and differentiation of the growth plate chondrocytes. Using a technique called spatial transcriptomics, we compared the gene expression profiles in control and Adgrg6 mutant growth plates and found that ADGRG6 prevents premature hypertrophic differentiation of the growth plate chondrocytes by negatively regulating Indian Hedgehog (IHH) signaling. In summary, our findings highlighted the essential role of a cartilage-enriched GPCR in maintaining growth plate homeostasis through IHH signaling.

Conserved signaling modules regulate filamentous growth in fungi: a model for eukaryotic cell differentiation.

Eukaryotic organisms are composed of different cell types with defined shapes and functions. Specific cell types are produced by the process of cell differentiation, which is regulated by signal transduction pathways. Signaling pathways regulate cell differentiation by sensing cues and controlling the expression of target genes whose products generate cell types with specific attributes. In studying how cells differentiate, fungi have proved valuable models because of their ease of genetic manipulation and striking cell morphologies. Many fungal species undergo filamentous growth-a specialized growth pattern where cells produce elongated tube-like projections. Filamentous growth promotes expansion into new environments, including invasion into plant and animal hosts by fungal pathogens. The same signaling pathways that regulate filamentous growth in fungi also control cell differentiation throughout eukaryotes and include highly conserved mitogen-activated protein kinase (MAPK) pathways, which is the focus of this review. In many fungal species, mucin-type sensors regulate MAPK pathways to control filamentous growth in response to diverse stimuli. Once activated, MAPK pathways reorganize cell polarity, induce changes in cell adhesion, and promote the secretion of degradative enzymes that mediate access to new environments. However, MAPK pathway regulation is complicated because related pathways can share components with each other yet induce unique responses (i.e. signal specificity). In addition, MAPK pathways function in highly integrated networks with other regulatory pathways (i.e. signal integration). Here, we discuss signal specificity and integration in several yeast models (mainly Saccharomyces cerevisiae and Candida albicans) by focusing on the filamentation MAPK pathway. Because of the strong evolutionary ties between species, a deeper understanding of the regulation of filamentous growth in established models and increasingly diverse fungal species can reveal fundamentally new mechanisms underlying eukaryotic cell differentiation.

International overview of sea turtle fibropapillomatosis: a survey of expert opinions and trends.

Introduction: Marine environments offer a wealth of opportunities to improve understanding and treatment options for cancers, through insights into a range of fields from drug discovery to mechanistic insights. By applying One Health principles the knowledge obtained can benefit both human and animal populations, including marine species suffering from cancer. One such species is green sea turtles (Chelonia mydas), which are under threat from fibropapillomatosis (FP), an epizootic tumor disease (animal epidemic) that continues to spread and increase in prevalence globally. In order to effectively address this epizootic, a more thorough understanding is required of the prevalence of the disease and the approaches to treating afflicted turtles. Methods: To identify knowledge gaps and assess future needs, we conducted a survey of sea turtle FP experts. The survey consisted of 47 questions designed to assess general perceptions of FP, the areas where more information is needed, local FP trends, the disease status, and mitigation needs, and was voluntarily completed by 44 experts across a broad geographic range. Results: Over 70% of respondents both recognized FP as a cancerous panzootic disease, and reported that FP is increasing in prevalence. They report several factors contributing to this increase. Nearly all of the respondents reported that FP research, patient treatment and rehabilitation required more funding in their area, and reported inadequate facilities and capacity for dealing with FP patients. Treatment approaches varied: just over 70% of the medical experts that responded surgically remove FP tumors, either using laser or scalpel. Just under half of respondents use anti-cancer drugs in their treatment of FP. Internal tumors were reported as justification for euthanasia by 61.5% of respondents, and 30.8% reported severe external tumors to be sufficient grounds for euthanasia. Most medical respondents (93.3%) routinely perform necropsy on deceased or euthanized FP-afflicted turtles. Over 80% of respondents considered large-scale multidisciplinary collaboration 'extremely important' for advancing the field of FP research. Discussion: The survey responses provide a valuable insight into the current status of FP in sea turtles, FP treatment, rehabilitation and research, and help to identify critical FP-related areas most in need of attention.

The protein domains of vertebrate species in which selection is more effective have greater intrinsic structural disorder.

The nearly neutral theory of molecular evolution posits variation among species in the effectiveness of selection. In an idealized model, the census population size determines both this minimum magnitude of the selection coefficient required for deleterious variants to be reliably purged, and the amount of neutral diversity. Empirically, an 'effective population size' is often estimated from the amount of putatively neutral genetic diversity and is assumed to also capture a species' effectiveness of selection. A potentially more direct measure of the effectiveness of selection is the degree to which selection maintains preferred codons. However, past metrics that compare codon bias across species are confounded by among-species variation in %GC content and/or amino acid composition. Here, we propose a new Codon Adaptation Index of Species (CAIS), based on Kullback-Leibler divergence, that corrects for both confounders. We demonstrate the use of CAIS correlations, as well as the Effective Number of Codons, to show that the protein domains of more highly adapted vertebrate species evolve higher intrinsic structural disorder.

Evolution is the process through which populations change over time, starting with mutations in the genetic sequence of an organism. Many of these mutations harm the survival and reproduction of an organism, but only by a very small amount. Some species, especially those with large populations, can purge these slightly harmful mutations more effectively than other species. This fact has been used by the 'drift barrier theory' to explain various profound differences amongst species, including differences in biological complexity. In this theory, the effectiveness of eliminating slightly harmful mutations is specified by an 'effective' population size, which depends on factors beyond just the number of individuals in the population. Effective population size is normally calculated from the amount of time a 'neutral' mutation (one with no effect at all) stays in the population before becoming lost or taking over. Estimating this time requires both representative data for genetic diversity and knowledge of the mutation rate. A major limitation is that these data are unavailable for most species. A second limitation is that a brief, temporary reduction in the number of individuals has an oversized impact on the metric, relative to its impact on the number of slighly harmful mutations accumulated. Weibel, Wheeler et al. developed a new metric to more directly determine how effectively a species purges slightly harmful mutations. Their approach is based on the fact that the genetic code has 'synonymous' sequences. These sequences code for the same amino acid building block, with one of these sequences being only slightly preferred over others. The metric by Weibel, Wheeler et al. quantifies the proportion of the genome from which less preferred synonymous sequences have been effectively purged. It judges a population to have a higher effective population size when the usage of synonymous sequences departs further from the usage predicted from mutational processes. The researchers expected that natural selection would favour 'ordered' proteins with robust three-dimensional structures, i.e., that species with a higher effective population size would tend to have more ordered versions of a protein. Instead, they found the opposite: species with a higher effective population size tend to have more disordered versions of the same protein. This changes our view of how natural selection acts on proteins. Why species are so different remains a fundamental question in biology. Weibel, Wheeler et al. provide a useful tool for future applications of drift barrier theory to a broad range of ways that species differ.

Early moderate prenatal alcohol exposure and maternal diet impact offspring DNA methylation across species.

Alcohol consumption in pregnancy can affect genome regulation in the developing offspring but results have been contradictory. We employed a physiologically relevant murine model of short-term moderate prenatal alcohol exposure (PAE) resembling common patterns of alcohol consumption in pregnancy in humans. Early moderate PAE was sufficient to affect site-specific DNA methylation in newborn pups without altering behavioural outcomes in adult littermates. Whole-genome bisulfite sequencing of neonatal brain and liver revealed stochastic influence on DNA methylation that was mostly tissue-specific, with some perturbations likely originating as early as gastrulation. DNA methylation differences were enriched in non-coding genomic regions with regulatory potential indicative of broad effects of alcohol on genome regulation. Replication studies in human cohorts with fetal alcohol spectrum disorder suggested some effects were metastable at genes linked to disease-relevant traits including facial morphology, intelligence, educational attainment, autism, and schizophrenia. In our murine model, a maternal diet high in folate and choline protected against some of the damaging effects of early moderate PAE on DNA methylation. Our studies demonstrate that early moderate exposure is sufficient to affect fetal genome regulation even in the absence of overt phenotypic changes and highlight a role for preventative maternal dietary interventions.

Drinking excessive amounts of alcohol during pregnancy can cause foetal alcohol spectrum disorder and other conditions in children that affect their physical and mental development. Many countries advise women who are pregnant or trying to conceive to avoid drinking alcohol entirely. However, surveys of large groups of women in Western countries indicate that most women continue drinking low to moderate amounts of alcohol until they discover they are pregnant and then stop consuming alcohol for the rest of their pregnancy. It remains unclear how this common drinking pattern affects the foetus. The instructions needed to build and maintain a human body are stored within molecules of DNA. Some regions of DNA called genes contain the instructions to make proteins, which perform many tasks in the body. Other so-called 'non-coding' regions do not code for any proteins but instead have roles in regulating gene activity. One way cells control which genes are switched on or off is adding or removing tags known as methyl groups to certain locations on DNA. Previous studies indicate that alcohol may affect how children develop by changing the patterns of methyl tags on DNA. To investigate the effect of moderate drinking during the early stages of pregnancy, Bestry et al. exposed pregnant mice to alcohol and examined how this affected the patterns of methyl tags on DNA in their offspring. The experiments found moderate levels of alcohol were sufficient to alter the patterns of methyl tags in the brains and livers of the newborn mice. Most of the changes were observed in non-coding regions of DNA, suggesting alcohol may affect how large groups of genes are regulated. Fewer changes in the patterns of methyl tags were found in mice whose mothers had diets rich in two essential nutrients known as folate and choline. Further experiments found that some of the affected mouse genes were similar to genes linked to foetal alcohol spectrum disorder and other related conditions in humans. These findings highlight the potential risks of consuming even moderate levels of alcohol during pregnancy and suggest that a maternal diet rich in folate and choline may help mitigate some of the harmful effects on the developing foetus.

Empowering AlphaFold2 for protein conformation selective drug discovery with AlphaFold2-RAVE.

Small-molecule drug design hinges on obtaining co-crystallized ligand-protein structures. Despite AlphaFold2's strides in protein native structure prediction, its focus on apo structures overlooks ligands and associated holo structures. Moreover, designing selective drugs often benefits from the targeting of diverse metastable conformations. Therefore, direct application of AlphaFold2 models in virtual screening and drug discovery remains tentative. Here, we demonstrate an AlphaFold2-based framework combined with all-atom enhanced sampling molecular dynamics and Induced Fit docking, named AF2RAVE-Glide, to conduct computational model-based small-molecule binding of metastable protein kinase conformations, initiated from protein sequences. We demonstrate the AF2RAVE-Glide workflow on three different mammalian protein kinases and their type I and II inhibitors, with special emphasis on binding of known type II kinase inhibitors which target the metastable classical DFG-out state. These states are not easy to sample from AlphaFold2. Here, we demonstrate how with AF2RAVE these metastable conformations can be sampled for different kinases with high enough accuracy to enable subsequent docking of known type II kinase inhibitors with more than 50% success rates across docking calculations. We believe the protocol should be deployable for other kinases and more proteins generally.

Reversions mask the contribution of adaptive evolution in microbiomes.

When examining bacterial genomes for evidence of past selection, the results depend heavily on the mutational distance between chosen genomes. Even within a bacterial species, genomes separated by larger mutational distances exhibit stronger evidence of purifying selection as assessed by dN/dS, the normalized ratio of nonsynonymous to synonymous mutations. Here, we show that the classical interpretation of this scale dependence, weak purifying selection, leads to problematic mutation accumulation when applied to available gut microbiome data. We propose an alternative, adaptive reversion model with opposite implications for dynamical intuition and applications of dN/dS. Reversions that occur and sweep within-host populations are nearly guaranteed in microbiomes due to large population sizes, short generation times, and variable environments. Using analytical and simulation approaches, we show that adaptive reversion can explain the dN/dS decay given only dozens of locally fluctuating selective pressures, which is realistic in the context of Bacteroides genomes. The success of the adaptive reversion model argues for interpreting low values of dN/dS obtained from long timescales with caution as they may emerge even when adaptive sweeps are frequent. Our work thus inverts the interpretation of an old observation in bacterial evolution, illustrates the potential of mutational reversions to shape genomic landscapes over time, and highlights the importance of studying bacterial genomic evolution on short timescales.

ImmCellTyper facilitates systematic mass cytometry data analysis for deep immune profiling.

Mass cytometry is a cutting-edge high-dimensional technology for profiling marker expression at the single-cell level, advancing clinical research in immune monitoring. Nevertheless, the vast data generated by cytometry by time-of-flight (CyTOF) poses a significant analytical challenge. To address this, we describe ImmCellTyper (https://github.com/JingAnyaSun/ImmCellTyper), a novel toolkit for CyTOF data analysis. This framework incorporates BinaryClust, an in-house developed semi-supervised clustering tool that automatically identifies main cell types. BinaryClust outperforms existing clustering tools in accuracy and speed, as shown in benchmarks with two datasets of approximately 4 million cells, matching the precision of manual gating by human experts. Furthermore, ImmCellTyper offers various visualisation and analytical tools, spanning from quality control to differential analysis, tailored to users' specific needs for a comprehensive CyTOF data analysis solution. The workflow includes five key steps: (1) batch effect evaluation and correction, (2) data quality control and pre-processing, (3) main cell lineage characterisation and quantification, (4) in-depth investigation of specific cell types; and (5) differential analysis of cell abundance and functional marker expression across study groups. Overall, ImmCellTyper combines expert biological knowledge in a semi-supervised approach to accurately deconvolute well-defined main cell lineages, while maintaining the potential of unsupervised methods to discover novel cell subsets, thus facilitating high-dimensional immune profiling.

The SW480 cell line as a model of resident and migrating colon cancer stem cells.

Intra-tumor heterogeneity, i.e., the presence of diverse cell types and subpopulations within tumors, presents a significant obstacle in cancer treatment due to its negative consequences for resistance to therapy and disease recurrence. However, the mechanisms that underlie intra-tumor heterogeneity and result in the plethora of different cancer cells within a single lesion remain poorly understood. Here, we leverage the SW480 cell line as a model system to investigate the molecular and functional diversity of colon cancer cells. Through a combination of fluorescence-activated cell sorting (FACS) analysis and transcriptomic profiling, we identified three distinct subpopulations, namely resident cancer stem cells (rCSCs), migratory CSCs (mCSCs), and high-relapse cells (HRCs). These subpopulations show varying Wnt signaling levels and gene expression profiles mirroring their stem-like and functional properties. Examination of publicly available spatial transcriptomic data confirms the presence of these subpopulations in patient-derived cancers and reveals their distinct spatial distribution relative to the tumor microenvironment.

Dynamic remodeling of septin structures fine-tunes myogenic differentiation.

Controlled myogenic differentiation is integral to the development, maintenance and repair of skeletal muscle, necessitating precise regulation of myogenic progenitors and resident stem cells. The transformation of proliferative muscle progenitors into multinuclear syncytia involves intricate cellular processes driven by cytoskeletal reorganization. While actin and microtubles have been extensively studied, we illuminate the role of septins, an essential yet still often overlooked cytoskeletal component, in myoblast architecture. Notably, Septin9 emerges as a critical regulator of myoblast differentiation during the initial commitment phase. Knock-down of Septin9 in C2C12 cells and primary mouse myoblasts accelerates the transition from proliferation to committed progenitor transcriptional programs. Furthermore, we unveil significant reorganization and downregulation of Septin9 during myogenic differentiation. Collectively, we propose that filmamentous septin structures and their orchestrated reorganization in myoblasts are part of a temporal regulatory mechanism governing the differentiation of myogenic progenitors. This study sheds light on the dynamic interplay between cytoskeletal components underlying controlled myogenic differentiation.

Human RP105 monoclonal antibody enhances antigen-specific antibody production in unique culture conditions.

Detecting antibodies, particularly those targeting donor human leukocyte antigens in organ transplantation and self-antigens in autoimmune diseases, is crucial for diagnosis and therapy. Radioprotective 105 (RP105), a Toll-like receptor family protein, is expressed in immune-competent cells, such as B cells. Studies in mice have shown that the anti-mouse RP105 antibody strongly activates B cells and triggers an adjuvant effect against viral infections. However, the anti-human RP105 antibody (ɑhRP105) weakly activates human B cells. This study established new culture conditions under, which human B cells are strongly activated by the ɑhRP105. When combined with CpGDNA, specific antibody production against blood group carbohydrates, ɑGal, and SARS-CoV-2 was successfully detected in human B cell cultures. Furthermore, comprehensive analysis using liquid chromatography-electrospray ionization tandem mass spectrometry, single-cell RNA sequencing, and quantitative real-time PCR revealed that ɑhRP105 triggered a different activation stimulus compared to CpGDNA. These findings could help identify antibody-producing B cells in cases of transplant rejection and autoimmune diseases.

HMGB2 drives tumor progression and shapes the immunosuppressive microenvironment in hepatocellular carcinoma: insights from multi-omics analysis.

Background: Hepatocellular carcinoma (HCC) poses a significant health burden globally, with high mortality rates despite various treatment options. Immunotherapy, particularly immune-checkpoint inhibitors (ICIs), has shown promise, but resistance and metastasis remain major challenges. Understanding the intricacies of the tumor microenvironment (TME) is imperative for optimizing HCC management strategies and enhancing patient prognosis. Methods: This study employed a comprehensive approach integrating multi-omics approaches, including single-cell RNA sequencing (scRNA-seq), bulk RNA sequencing (Bulk RNA-seq), and validation in clinical samples using spatial transcriptomics (ST) and multiplex immunohistochemistry (mIHC). The analysis aimed to identify key factors influencing the immunosuppressive microenvironment associated with HCC metastasis and immunotherapy resistance. Results: HMGB2 is significantly upregulated in HCCTrans, a transitional subgroup associated with aggressive metastasis. Furthermore, HMGB2 expression positively correlates with an immunosuppressive microenvironment, particularly evident in exhausted T cells. Notably, HMGB2 expression correlated positively with immunosuppressive markers and poor prognosis in HCC patients across multiple cohorts. ST combined with mIHC validated the spatial expression patterns of HMGB2 within the TME, providing additional evidence of its role in HCC progression and immune evasion. Conclusion: HMGB2 emerges as a critical player of HCC progression, metastasis, and immunosuppression. Its elevated expression correlates with aggressive tumor behavior and poor patient outcomes, suggesting its potential as both a therapeutic target and a prognostic indicator in HCC management.

Omics approaches to unravel insecticide resistance mechanism in Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae).

Bemisia tabaci (Gennadius) whitefly (BtWf) is an invasive pest that has already spread worldwide and caused major crop losses. Numerous strategies have been implemented to control their infestation, including the use of insecticides. However, prolonged insecticide exposures have evolved BtWf to resist these chemicals. Such resistance mechanism is known to be regulated at the molecular level and systems biology omics approaches could shed some light on understanding this regulation wholistically. In this review, we discuss the use of various omics techniques (genomics, transcriptomics, proteomics, and metabolomics) to unravel the mechanism of insecticide resistance in BtWf. We summarize key genes, enzymes, and metabolic regulation that are associated with the resistance mechanism and review their impact on BtWf resistance. Evidently, key enzymes involved in the detoxification system such as cytochrome P450 (CYP), glutathione S-transferases (GST), carboxylesterases (COE), UDP-glucuronosyltransferases (UGT), and ATP binding cassette transporters (ABC) family played key roles in the resistance. These genes/proteins can then serve as the foundation for other targeted techniques, such as gene silencing techniques using RNA interference and CRISPR. In the future, such techniques will be useful to knock down detoxifying genes and crucial neutralizing enzymes involved in the resistance mechanism, which could lead to solutions for coping against BtWf infestation.

Efficient production of phenyllactic acid in Escherichia coli via metabolic engineering and fermentation optimization strategies.

Phenyllactic acid (PhLA), an important natural organic acid, can be used as a biopreservative, monomer of the novel polymeric material poly (phenyllactic acid), and raw material for various medicines. Herein, we achieved a high-level production of PhLA in Escherichia coli through the application of metabolic engineering and fermentation optimization strategies. First, the PhLA biosynthetic pathway was established in E. coli CGSC4510, and the phenylalanine biosynthetic pathway was disrupted to improve the carbon flux toward PhLA biosynthesis. Then, we increased the copy number of the key genes involved in the synthesis of the PhLA precursor phenylpyruvic acid. Concurrently, we disrupted the tryptophan biosynthetic pathway and enhanced the availability of phosphoenolpyruvate and erythrose 4-phosphate, thereby constructing the genetically engineered strain MG-P10. This strain was capable of producing 1.42 ± 0.02 g/L PhLA through shake flask fermentation. Furthermore, after optimizing the dissolved oxygen feedback feeding process and other conditions, the PhLA yield reached 52.89 ± 0.25 g/L in a 6 L fermenter. This study successfully utilized metabolic engineering and fermentation optimization strategies to lay a foundation for efficient PhLA production in E. coli as an industrial application.