Biology subjects

Shen, Y.

Publications and source records attributed to Shen, Y..

At least 253 records · Page 14Linked to original sources

bioRxiv2023

Ultrasensitive Proteomics Depicted an In-depth Landscape for Mouse Embryo

In recent years, single-cell or low-input multi-omics techniques have brought a revolution in the study of pre-implantation embryo development. However, single-cell or low-input proteome research in this field is relatively underdeveloped, due to the limited source of mammalian embryo samples, the objective reality of high abundance zona pellucida proteins, and the lack of hypersensitive proteome technology. Here, a comprehensive solution of ultrasensitive proteome technology was developed for single-cell or low-input mouse embryos. Both deep coverage route and high-throughput route could significantly reduce the starting material and enhance the proteomic depth without any customized instrument. Using the deep coverage route, an average of 2,665 or 4,585 protein groups can be identified from 1 or 20 mouse zygotes respectively. Using the high-throughput route, 300 single mouse zygotes can be analysis in 8 days with an average of 2,371 proteins identified. With its popularization, we believe researchers can choose deep coverage or high-throughput technology routes according to their own conditions.

systems biology↗

bioRxiv2023

ErbB inhibition impairs cognition via disrupting myelination and aerobic glycolysis in oligodendrocytes

White matter abnormalities are an emerging feature of schizophrenia, yet the underlying pathophysiological mechanisms are largely unknown. Disruption of ErbB signaling that is essential for peripheral myelination has been genetically associated with schizophrenia and white matter lesions in schizophrenic patients. However, the roles of ErbB signaling in oligodendrocytes remain elusive. Here, we used a pan-ErbB inhibition strategy and demonstrated the synergistic functions of endogenous ErbB receptors in oligodendrocytes. Through analyses of the cellular, histological, biochemical, behavioral, and electrophysiological differences in mice with manipulation of ErbB activities in oligodendrocytes at different differentiation stages, we found that ErbB signaling regulates myelination and aerobic glycolysis in oligodendrocytes, and both functions are required for working memory. ErbB inhibition in oligodendrocytes at early differentiation stages induces hypomyelination by suppressing the differentiation of newly-formed oligodendrocytes. In contrast, ErbB inhibition in mature oligodendrocytes alters neither myelination nor oligodendrocyte numbers, but accelerates axonal conduction decline under energy stress. Mechanistically, mature oligodendrocytes with ErbB inhibition reduce the expression of lactate dehydrogenase A, failing to provide lactate to electrically active axons. Supplementation of L-lactate restores axonal conduction and working memory capacity that are suppressed by ErbB inhibition in mature oligodendrocytes. These findings reveal the indispensable roles of ErbB signaling in white matter integrity and function, and provide insights into the multifaceted contributions of white matter abnormalities to cognitive impairment.

neuroscience↗

bioRxiv2022

Translating Membrane Geometry into Protein Function: Multifaceted Membrane Interactions of Human Atg3 Promote LC3-Phosphatidylethanolamine Conjugation during Autophagy

Autophagosome formation is the hallmark of macroautophagy (herein referred to as autophagy) and requires the covalent conjugation of LC3 proteins (or Atg8 in yeast) to the amino headgroup of PE (phosphatidylethanolamine) lipids. Atg3 is an enzyme that catalyzes the final step of this reaction by transferring LC3 from an LC3-Atg3 intermediate to PEs in targeted membranes. Here, we determine the solution structure of human Atg3 (hAtg3) and demonstrate that the catalytically important regions of hAtg3 are conformationally dynamic. Furthermore, we reveal that these regions and hAtg3s N-terminal membrane curvature-sensing amphipathic helix concurrently interact with the membrane. These structural studies indicate that hAtg3 exploits a multifaceted membrane-association mechanism to position its catalytic center at the membrane surface and to bring the reaction substrates of LC3 and PE lipids to proximity for effective LC3-PE conjugation. In addition, our studies demonstrate that the interaction of the His266 residue with the membrane is primarily responsible for hAtg3s pH-dependent activity. Our investigations advance an emerging concept that the interactions of Atg3 with the highly curved membrane rims of the phagophore spatially regulate autophagosome biogenesis.

biochemistry↗

bioRxiv2022

Multi-center integrated analysis of non-coding CRISPR screens

The ENCODE Consortiums efforts to annotate non-coding, cis-regulatory elements (CREs) have advanced our understanding of gene regulatory landscapes which play a major role in health and disease. Pooled, non-coding CRISPR screens are a promising approach for systematically investigating gene regulatory mechanisms. Here, the ENCODE Functional Characterization Centers report 109 screens comprising 346,970 individual perturbations across 13.3Mb of the genome, using a variety of methods, readouts, and statistical analyses. Across 332 functionally confirmed CRE-gene links, we identify principles for screening endogenous, non-coding elements for causal regulatory mechanisms. Nearly all CREs show strong evidence of open chromatin, and targeting accessibility peak summits is a critical component of our proposed sgRNA design rules. We provide experimental guidelines to accurately detect CREs with variable, often low, transcriptional effects. We discover a previously undescribed DNA strand-bias for CRISPRi in transcribed regions with implications for screen design and analysis. Benchmarking five screen analysis tools, we find CASA produces the most conservative CRE calls and is robust to artifacts of low-specificity sgRNAs. Together, we provide an accessible data resource, predesigned sgRNAs targeting 3,275,697 ENCODE SCREEN candidate CREs, and screening guidelines to accelerate functional characterization of the non-coding genome.

genomics↗

bioRxiv2022

Multimodal learning of noncoding variant effects using genome sequence and chromatin structure

MotivationA growing amount of noncoding genetic variants, including single-nucleotide polymorphisms (SNPs), are found to be associated with complex human traits and diseases. Their mechanistic interpretation is relatively limited and can use the help from computational prediction of their effects on epigenetic profiles. However, current models often focus on local, 1D genome sequence determinants and disregard global, 3D chromatin structure that critically affects epigenetic events. ResultsWe find that noncoding variants of unexpected high similarity in epigenetic profiles, with regards to their relatively low similarity in local sequences, can be largely attributed to their proximity in chromatin structure. Accordingly we have developed a multimodal deep learning scheme that incorporates both data of 1D genome sequence and 3D chromatin structure for predicting noncoding variant effects. Specifically, we have integrated convolutional and recurrent neural networks for sequence embedding and graph neural networks for structure embedding despite the resolution gap between the two types of data, while utilizing recent DNA language models. Numerical results show that our models outperform competing sequence-only models in predicting epigenetic profiles and their use of long-range interactions complement sequence-only models in extracting regulatory motifs. They prove to be excellent predictors for noncoding variant effects in gene expression and pathogenicity, whether in unsupervised "zero-shot" learning or supervised "few-shot" learning. AvailabilityCodes and data access can be found at https://github.com/Shen-Lab/ncVarPred-1D3D Contactyshen@tamu.edu Supplementary informationSupplementary data are available at Bioinformatics online.

bioinformatics↗

bioRxiv2022

Structural basis for the assembly of the DNA polymerase holoenzyme from a monkeypox virus variant

The ongoing pandemic caused by a monkeypox virus (MPXV) variant has spread all over the world and raised great public health concerns. The DNA polymerase F8 of MPXV, associated with its processivity factors A22 and E4, is responsible for viral genome replication in the perinuclear sites of the infected cells as well as a critical target for developing antiviral drugs. However, the assembly and working mechanism for the DNA polymerase holoenzyme of MPXV remains elusive. Here, we present the cryo-EM structure of the DNA polymerase holoenzyme F8/A22/E4 from the 2022 West African strain at an overall resolution of 3.5 [A] and revealed the precise spatial arrangement. Surprisingly, unlike any other previously reported B-family DNA polymerase, the holoenzyme complex is assembled as a dimer of heterotrimers, of which the extra interface between the thumb domain of F8 and A22 shows a clash between A22 and substrate DNA, suggesting an auto-inhibition state. Supplying an exogenous double-stranded DNA could notably shift the hexameric form into a trimeric form, which exposes the DNA binding site of thumb domain and might represent a more active state. The structures provide a molecular basis for the design of new antiviral therapeutics that target the MPXV DNA polymerase holoenzyme.

biochemistry↗

bioRxiv2022

Role of HAO2 in rats with chronic kidney disease by regulating fatty acid metabolic processes in renal tissue

Fibrosis is a progressive, often irreversible histologic manifestation of chronic and end-stage renal disease. In this study, single-cell transcriptome sequencing technology was used to sequence and analyze blood and kidney tissue cells in normal control rats and rats with chronic kidney disease (CKD), focusing on key cell populations and functional enrichment to explore the pathogenesis of CKD. Oil red O staining and ELISA were used to detect lipid droplets and free fat acid (FFA). RT-PCR, WB were used to verify the differential gene HAO2 and fatty acid metabolic process in tissue to ensure the reliability of single-cell sequencing results. We successfully established a single-cell transcriptome atlas of blood and kidney tissue in rats with CKD, which were annotated into 14 cell subsets (MPCs, PT, Tc, DCT, B-IC, A-IC, CNT, ALOH, BC, Neu, Endo, Pla, NKT, Baso) according to marker gene, and the integrated single-cell atlas of rats showed a significant increase and decrease of MPCs and PTs in the model group, respectively. Functional analysis found extensive enrichment of metabolic-related pathways in PT cells, includes fatty acid metabolic process, cellular amino acid metabolic process and generation of precursor metabolites and energy. Immunohistochemical experiments determined that the differential gene HAO2 was localized in the renal tubules, and its expression was significantly reduced in model group compared with control, and oil red O staining showed that lipid droplets increased in the model group. ELISA assay showed that ATP content decreased in the model group and FFA increased in the model group. ACOX1, PPAR, PGC1 were decreased in the model group, while genes and proteins were increased after overexpression of HAO2, and the AMPK and ACC phosphorylated proteins were increased. Therefore, HAO2 may be an important regulator of fatty acid metabolic processes in CKD, and overexpression of HAO2 can enhance fatty acid metabolism by promoting fatty acid oxidation pathway.

cancer biology↗

bioRxiv2022

Context-dependent functions of mitochondria protein quality control in lung

Aside from its role as the universal energy source of the cell, mitochondria also control many aspects of cell behavior. In an intact tissue, whether all cells require mitochondria function to the same extent, and how mitochondria insufficiency impacts cell behavior are poorly understood. Here we show that in the mouse lung epithelium, inactivation of LONP1, an energy ATP-dependent protease that functions in the mitochondria to degrade unfolded and misfolded proteins, led to mitochondria deficiency. In the naive epithelium of the developing lung, loss of Lonp1 obliterated cell proliferation and differentiation. In the adult airway epithelium during homeostasis, loss of Lonp1 led to selective death of terminally differentiated multiciliated cells, leading to a cascade of progenitor activation to replace lost cells. In the adult airway epithelium following influenza infection, loss of Lonp1 led to failure of airway progenitor migration into the damaged alveolar region. Bulk and single cell transcriptomic analysis revealed that one branch of the ER stress pathways, namely integrated stress response (ISR), is ectopically upregulated in mutants under all three conditions. Inactivation of core ISR transcription factor ATF4 in the Lonp1 mutant airway reversed abovementioned phenotypes. Taken together, our findings demonstrate that depending on a cellular context, intact mitochondria function is required in either progenitor or progeny cells, and is essential for cell proliferation, survival or migration in the mammalian lung.

cell biology↗

bioRxiv2022

Does Inter-Protein Contact Prediction Benefit from Multi-Modal Data and Auxiliary Tasks?

Approaches to in silico prediction of protein structures have been revolutionized by AlphaFold2, while those to predict interfaces between proteins are relatively underdeveloped, owing to the overly complicated yet relatively limited data of protein-protein complexes. In short, proteins are 1D sequences of amino acids folding into 3D structures, and interact to form assemblies to function. We believe that such intricate scenarios are better modeled with additional indicative information that reflects their multi-modality nature and multi-scale functionality. To improve binary prediction of inter-protein residue-residue contacts, we propose to augment input features with multi-modal representations and to synergize the objective with auxiliary predictive tasks. (i) We first progressively add three protein modalities into models: protein sequences, sequences with evolutionary information, and structure-aware intra-protein residue contact maps. We observe that utilizing all data modalities delivers the best prediction precision. Analysis reveals that evolutionary and structural information benefit predictions on the difficult and rigid protein complexes, respectively, assessed by the resemblance to native residue contacts in bound complex structures. (ii) We next introduce three auxiliary tasks via self-supervised pre-training (binary prediction of protein-protein interaction (PPI)) and multi-task learning (prediction of inter-protein residue-residue distances and angles). Although PPI prediction is reported to benefit from predicting inter-contacts (as causal interpretations), it is not found vice versa in our study. Similarly, the finer-grained distance and angle predictions did not appear to uniformly improve contact prediction either. This again reflects the high complexity of protein-protein complex data, for which designing and incorporating synergistic auxiliary tasks remains challenging.

bioinformatics↗

bioRxiv2022

De novo design of modular peptide binding proteins by superhelical matching

General approaches for designing sequence-specific peptide binding proteins would have wide utility in proteomics and synthetic biology. Although considerable progress has been made in designing proteins which bind to other proteins, the general peptide binding problem is more challenging as most peptides do not have defined structures in isolation, and to offset the loss in solvation upon binding the protein binding interface has to provide specific hydrogen bonds that complement the majority of the buried peptides backbone polar groups (1-3). Inspired by natural repeat protein-peptide complexes, and engineering efforts to alter their specificity (4-11), we describe a general approach for de novo design of proteins made out of repeating units that bind peptides with repeating sequences such that there is a one to one correspondence between repeat units on the protein and peptide. We develop a rapid docking plus geometric hashing method to identify protein backbones and protein-peptide rigid body arrangements that are compatible with bidentate hydrogen bonds between side chains on the protein and the backbone of the peptide (12); the remainder of the protein sequence is then designed using Rosetta to incorporate additional interactions with the peptide and drive folding to the desired structure. We use this approach to design, from scratch, alpha helical repeat proteins that bind six different tripeptide repeat sequences--PLP, LRP, PEW, IYP, PRM and PKW--in near polyproline 2 helical conformations. The proteins are expressed at high levels in E. coli, are hyperstable, and bind peptides with 4-6 copies of the target tripeptide sequences with nanomolar to picomolar affinities both in vitro and in living cells. Crystal structures reveal repeating interactions between protein and peptide interactions as designed, including a ladder of protein sidechain to peptide backbone hydrogen bonds. By redesigning the binding interfaces of individual repeat units, specificity can be achieved for non-repeating sequences, and for naturally occuring proteins containing disordered regions. Our approach provides a general route to designing specific binding proteins for a broad range of repeating and non-repetitive peptide sequences.

biochemistry↗

bioRxiv2022

A Semi-Supervised Ensemble Approach to Rank Potential Causal Variants and Their Target Genes in Microglia for Alzheimer's Disease

Alzheimers disease (AD) is the leading cause of death among individuals over 65. Despite many AD genetic variants detected by large genome-wide association studies (GWAS), a limited number of causal genes have been confirmed. Conventional machine learning techniques integrate functional annotation data and GWAS signals to assign variants functional relevance probabilities. Yet, a large proportion of genetic variation lies in the non-coding genome, where unsupervised and semi-supervised techniques have demonstrated greater advantage. Furthermore, cell-type specific approaches are needed to better understand disease etiology. Studying AD from a microglia-specific lens is more likely to reveal causal variants involved in immune pathways. Therefore, in this study, we developed S-BEAM: a semi-supervised ensemble approach using microglia-specific data to prioritize non-coding variants and their target genes that play roles in immune-related AD mechanisms. We designed a transductive positive-unlabeled and negative-unlabeled learning model that employs a bagging technique to learn from unlabeled variants, generating multiple predicted probabilities of variant risk. Using a combined homogeneous-heterogeneous ensemble framework, we aggregated the predictions. We applied our model to AD variant data, identifying 11 risk variants acting in well-known AD genes, such as TSPAN14, INPP5D, and MS4A2. These results validated our models performance and demonstrated a need to study these genes in the context of microglial pathways. We also proposed further experimental study for 37 potential causal variants associated with less-known genes. Our work has utility in predicting AD relevant genes and variants functioning in microglia and can be generalized for application to other complex diseases or cell types.

genomics↗

bioRxiv2022

An armored marine reptile from the Early Triassic of South China

Sauropterygia was a taxonomically and ecomorphologically diverse clade of Mesozoic marine reptiles spanning the Early Triassic to the Late Cretaceous. Sauropterygians are traditionally divided into two groups representing two markedly different body plans - the short-necked, durophagous Placodontia and the long-necked Eosauropterygia - whereas Saurosphargidae, a small clade of marine reptiles possessing a dorsal rib-basket, is considered as the sauropterygian sister-group. However, the early evolutionary history of sauropterygians and their phylogenetic relationships with other groups within Diapsida are still incompletely understood. Here, we report a new saurosphargid from the Early Triassic of South China - Prosaurosphargis yingzishanensis gen. et sp. nov. - representing the earliest known occurrence of the clade. An updated phylogenetic analysis focussing on the interrelationships within diapsid reptiles recovers saurosphargids as nested within sauropterygians, forming a clade with eosauropterygians to the exclusion of placodonts. Furthermore, a clade comprising Eusaurosphargis and Palatodonta is recovered as the sauropterygian sister-group within Sauropterygomorpha tax. nov. The phylogenetic position of several Early and Middle Triassic sauropterygians of previously uncertain phylogenetic affinity, such as Atopodentatus, Hanosaurus, Majiashanosaurus and Corosaurus, is also clarified, elucidating the early evolutionary assembly of the sauropterygian body plan. Finally, our phylogenetic analysis recovers Testudinata and Archosauromorpha within Archelosauria, a result strongly supported by molecular data, but until now not recovered by any phylogenetic analysis using a morphology-only data set. Our study provides evidence for the rapid diversification of sauropterygians in the aftermath of the Permo-Triassic mass extinction event and emphasises the importance of broad taxonomic sampling in reconstructing phylogenetic relationships among extinct taxa.

paleontology↗

bioRxiv2022

The Serotonergic Neural Circuit Between The Dorsal Raphe Nucleus And The Basolateral Amygdala Is Implicated In Modulating The Arousal from Sevoflurane Anesthesia

Although some advancements concerning the arousal involved in mediating the delayed emergency from general anesthesia, which will lead to the serious complications, had been made, the role by arousal in modulating in delayed emergency still remains to be unclear. In our models, based on our previous working that activation of the 5-Hydroxytryptamine (5-HT) neurons in the dorsal raphe nucleus (DRN) by optogenetics can significantly reduce the emergency time by activating arousal pathway, we further test whether the serotonergic neural circuit between the DRN and the basolateral amygdala (BLA) is implicated in modulating the arousal from the sevoflurane anesthesia and the emergency time of sevoflurane anesthesia by the pharmacological, optogenetics and fiber photometry. Our findings showed that whether the serotonergic neural circuit between the DRN and the basolateral amygdala (BLA) plays a key role in modulating the arousal from the sevoflurane anesthesia and the emergency time of sevoflurane anesthesia. Based on the serotonergic neural circuit, the 5-HT 1 A receptor is of great significance to mediate the arousal and the emergency time of the sevoflurane anesthesia. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=143 SRC="FIGDIR/small/511924v2_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@34621eorg.highwire.dtl.DTLVardef@115ae09org.highwire.dtl.DTLVardef@54eb12org.highwire.dtl.DTLVardef@11515ff_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure1C_FLOATNO C_FIG

neuroscience↗

bioRxiv2022

Design, Construction, and Functional Characterization of a tRNA Neochromosome in Yeast

Here we report the design, construction and characterization of a tRNA neochromosome, a designer chromosome that functions as an additional, de novo counterpart to the native complement of Saccharomyces cerevisiae. Intending to address one of the central design principles of the Sc2.0 project, the [~]190 kb tRNA neochromosome houses all 275 relocated nuclear tRNA genes. To maximize stability, the design incorporated orthogonal genetic elements from non-S. cerevisiae yeast species. Furthermore, the presence of 283 rox recombination sites enable an orthogonal SCRaMbLE system capable of adjusting tRNA abundance. Following construction, we obtained evidence of a potent selective force once the neochromosome was introduced into yeast cells, manifesting as a spontaneous doubling in cell ploidy. Furthermore, tRNA sequencing, transcriptomics, proteomics, nucleosome mapping, replication profiling, FISH and Hi-C were undertaken to investigate questions of tRNA neochromosome behavior and function. Its construction demonstrates the remarkable tractability of the yeast model and opens up new opportunities to directly test hypotheses surrounding these essential non-coding RNAs. HighlightsO_LIDe novo design, construction and functional characterization of a neochromosome containing all 275 nuclear tRNA genes of Saccharomyces cerevisiae. C_LIO_LIIncreasing the copy number of the 275 highly expressed tRNA genes causes cellular burden, which the host cell likely buffers either by selecting for partial tRNA neochromosome deletions or by increasing its ploidy. C_LIO_LIThe tRNA neochromosome can be chemically extracted and transformed into new strain backgrounds, enabling its transplantation into multi-synthetic chromosome strains to finalize the Sc2.0 strain. C_LIO_LIComprehensive functional characterization does not pinpoint a singular cause for the cellular burden caused by the tRNA neochromosome, but does reveal novel insights into its tRNA and structural chromosome biology. C_LI

synthetic biology↗

bioRxiv2022

LKB1 loss rewires JNK-induced apoptotic protein dynamics through NUAKs and sensitizes KRAS-mutant NSCLC to combined KRASG12C + MCL-1 blockade

The efficacy of molecularly targeted anti-cancer therapies may be limited by the presence of co-occurring mutations within a tumor1-3. Conversely, these alterations may confer collateral vulnerabilities that can be leveraged for the development of novel therapeutic approaches. KRAS-mutant lung cancers are distinguished by recurrent inactivating mutations in the tumor suppressor STK11/LKB14 that facilitate tumorigenesis by modulating energy balance5, 6, enhancing metastatic potential7,8 and enabling immune evasion9,10. However, whether LKB1 plays a role in modulating cellular responses to therapeutic stress is largely unknown. Here we show that LKB1 suppresses JNK-dependent stress signaling in KRAS-mutant lung cancer cells upon acute loss of oncogenic signaling. In LKB1-deficient KRAS-mutant cells, inhibition of KRAS or its downstream effector MEK leads to hyperactivation of JNK due to loss of NUAK-mediated PP1B phosphatase activity. JNK-mediated inhibitory phosphorylation of BCL-XL rewires apoptotic dependencies, rendering LKB1-deficient cells vulnerable to MCL-1 inhibition. These results uncover a previously unknown role for LKB1 in regulating stress signaling and the mitochondrial apoptotic response of cancer cells independent of its tumor suppressor activity mediated by AMPK11-13 and SIK14,15 kinases. Additionally, our study reveals a therapy-induced vulnerability in LKB1-deficient KRAS-mutant lung cancer cells that could be exploited as a genotype-informed strategy to improve the efficacy of KRAS-targeted therapies.

cancer biology↗

bioRxiv2022

SHINE: Protein Language Model based Pathogenicity Prediction for Inframe Insertion and Deletion Variants

Inframe insertion and deletion variants (indels) alter protein sequence and length. Accurate pathogenicity predictions are important in genetic studies of human diseases. Indel Interpretation is challenging due to limitations in the available number of known pathogenic variants for training. Existing methods largely use manually encoded features including conservation, protein structure and function, and allele frequency. Recent advances in deep learning modeling of protein sequences and structures provide an opportunity to improve the representation of salient features based on large numbers of protein sequences. We developed a new pathogenicity predictor for SHort Inframe iNsertion and dEletion (SHINE). SHINE uses pre-trained protein language models to construct a latent representation of an indel and its protein context from protein sequences and multiple protein sequence alignments, and feeds the latent representation into supervised machine learning models for pathogenicity prediction. We curated training data from ClinVar and gnomAD, and created two test datasets from different sources. SHINE achieved better prediction performance than existing methods for both deletion and insertion variants in these two test datasets. Our work suggests that unsupervised protein language models can provide valuable information about proteins, and new methods based on these models can improve variant interpretation in genetic analyses.

bioinformatics↗

bioRxiv2022

Dissecting aneuploidy phenotypes by constructing Sc2.0 chromosome VII and SCRaMbLEing synthetic disomic yeast

Aneuploidy compromises genomic stability, often leading to embryo inviability, and is frequently associated with tumorigenesis and aging. Different aneuploid chromosome stoichiometries lead to distinct transcriptomic and phenotypic changes, making it helpful to study aneuploidy in tightly controlled genetic backgrounds. By deploying the engineered SCRaMbLE system to the newly synthesized Sc2.0 megabase chromosome VII (synVII), we constructed a synthetic disomic yeast and screened hundreds of SCRaMbLEd derivatives with diverse chromosomal rearrangements. Phenotypic characterization and multi-omics analysis revealed that fitness defects associated with aneuploidy could be restored by i) removing most of the chromosome content, or ii) modifying specific regions in the duplicated chromosome. These findings indicate that both chromosome copy number and chromosomal regions contribute to the aneuploidy-related phenotypes, and the synthetic yeast resource opens new paradigms in studying aneuploidy. In briefUse of SCRaMbLE and newly synthesized Mb-scale Sc2.0 chromosome VII enables insights into genotype/phenotype relationships associated with aneuploidy HighlightsO_LIDe novo design and synthesis of a Mb-scale synthetic yeast chromosome VII, carrying 11.8% sequence modifications and representing nearly 10% of the yeast genome. C_LIO_LIA disomic yeast (n + synVII) is constructed for dissecting the aneuploidy phenotype C_LIO_LISCRaMbLE enables systematic exploration of regions causing aneuploidy phenotypes C_LIO_LIChromosomal copy number and content both contribute to aneuploidy phenotypes C_LIO_LIA 20 Kb deletion on the right arm of synVII leads to fitness improvement linked to up-regulation of protein synthesis C_LI

synthetic biology↗

bioRxiv2022

A Metabolic Sum Rule Dictates Bacterial Response to Short-Chain Fatty Acid Stress

Short-chain fatty acids (SCFAs) such as acetate accumulate in fermentative environments, inhibiting many types of bacteria. While it is known that cells accumulate SCFAs to high concentrations internally, the cause of SCFA toxicity is not understood. By forcing Escherichia coli cells to accumulate a variety of "useless metabolites", we establish via extensive omic analysis a metabolic sum rule, by which the accumulation of exogenous metabolites such as acetate forces the depletion of endogenous metabolites. The latter leads to bottlenecks in biosynthesis, manifested as a simple linear relation between useless metabolite accumulation and growth reduction. Guided by quantitative models, we show that acetate-stressed cells optimize growth by partially acidifying their own cytoplasm, which reduces acetate accumulation, restoring the endogenous metabolites as allowed by the sum rule.

microbiology↗