Biology subjects

Shi, H.

Publications and source records attributed to Shi, H..

At least 181 records · Page 10Linked to original sources

bioRxiv2021

A potent bispecific nanobody protects hACE2 mice against SARS-CoV-2 infection via intranasal administration

The dramatically expanding COVID-19 needs multiple effective countermeasures. Neutralizing antibodies are a potential therapeutic strategy for treating COVID-19. A number of neutralizing nanobodies (Nbs) were reported for their in vitro activities. However, in vivo protection of these nanobodies was not reported in animal models. In the current report, we characterized several RBD-specific Nbs isolated from a screen of an Nb library derived from an alpaca immunized with SARS-CoV-2 spike glycoprotein (S); among them, three Nbs exhibited picomolar potency against SARS-CoV-2 live virus, pseudotyped viruses, and 15 circulating SARS-CoV-2 variants. To improve the efficacy, various configurations of Nbs were engineered. Nb15-NbH-Nb15, a novel trimer constituted of three Nbs, was constructed to be bispecific for human serum albumin (HSA) and RBD of SARS-CoV-2. Nb15-NbH-Nb15 exhibited sub-ng/ml neutralization potency against the wild-type and currently circulating variants of SARS-CoV-2 with a long half-life in vivo. In addition, we showed that intranasal administration of Nb15-NbH-Nb15 provided 100% protection for both prophylactic and therapeutic purposes against SARS-CoV-2 infection in transgenic hACE2 mice. Nb15-NbH-Nb15 is a potential candidate for both prevention and treatment of SARS-CoV-2 through respiratory administration. One sentence summaryNb15-NbH-Nb15, with a novel heterotrimeric bispecific configuration, exhibited potent and broad neutralization potency against SARS-CoV-2 in vitro and provided in vivo protection against SARS-CoV-2 infection in hACE2 transgenic mice via intranasal delivery. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/429275v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@a30bc8org.highwire.dtl.DTLVardef@5a872eorg.highwire.dtl.DTLVardef@1610f74org.highwire.dtl.DTLVardef@13d9bd8_HPS_FORMAT_FIGEXP M_FIG Graphical abstract: C_FIG HighlightsO_LIWe described a novel heterotrimeric configuration of Nb-NbH-Nb (Nb15-NbH-Nb15) that exhibited improved viral inhibition and stability. C_LIO_LINb15-NbH-Nb15 provides ultrahigh neutralization potency against SARS-CoV-2 wild type and 18 mutant variants, including the current circulating variants of D614G and N501Y predominantly in the UK and South Africa. C_LIO_LIIt is the first to demonstrate the Nbs efficacy in preventing and treating SARS-CoV-2 infection in hACE2 transgenic mice via intranasal delivery. C_LI

microbiology↗

bioRxiv2021

Analysis of Spleen Histopathology, Splenocyte composition and Hematological Parameters in Mice Infected with Plasmodium berghei K173

Malaria is a fatal disease that presents clinically as a continuum of symptoms and severity, which are determined by complex host-parasite interactions. Clearance of infection is believed to be accomplished by the spleen and mononuclear phagocytic system (MPS), both in the presence and absence of artemisinin treatment. The spleen filters infected RBCs from circulation through immune-mediated recognition of the infected RBCs followed by phagocytosis. Using different strains of mice infected with P. berghei K173 (PbK173), the mechanisms leading to splenomegaly, histopathology, splenocyte activation and proliferation, and their relationship to control of parasitemia and host mortality were examined. Survival time of mice infected with PbK173 varied, although the infection was uniformly lethal. Mice of the C57BL/6 strain were the most resistant, while mice of the strain ICR were the most susceptible. BALB/c and KM mice were intermediate. In the course of PbK173 infection, both strains of mice experienced significant splenomegaly. Parasites were observed in the red pulp at 3 days post infection in all animals. All spleens retained late trophozoite stages as well as a fraction of earlier ring-stage parasites. The percentages of macrophages in infected C57BL/6 and KM mice were higher than uninfected mice on 8 dpi. Spleens of infected ICR and KM mice exhibited structural disorganization and remodeling. Furthermore, parasitemia was significantly higher in KM versus C57BL/6 mice at 8 dpi. The percentages of macrophages in ICR infected mice were lower than uninfected mice, and the parasitemia was higher than other strains. The results presented here demonstrate the rate of splenic mechanical filtration and the splenic macrophages likely contribute to an individuals total parasite burden. This in turn can influence the pathogenesis of malaria. Finally, different genetic backgrounds of mice have different splenic mechanisms for controlling malaria infection.

microbiology↗

bioRxiv2020

delta-Melt: Nucleic acid conformational penalties from melting experiments

Thermodynamic preferences to form non-native conformations are crucial for understanding how nucleic acids fold and function. However, they are difficult to measure experimentally because this requires accurately determining the population of minor low-abundance (<10%) conformations in a sea of other conformations. Here we show that melting experiments enable facile measurements of thermodynamic preferences to adopt non-native conformations in DNA and RNA. The key to this delta-melt approach is to use chemical modifications to render specific minor non-native conformations the major state. The validity and robustness of delta-melt is established for four different non-native conformations under various physiological conditions and sequence contexts through independent measurements of thermodynamic preferences using NMR. delta-melt is fast, simple, cost-effective, and enables thermodynamic preferences to be measured for exceptionally low-populated conformations. Using delta-melt, we obtained rare insights into conformational cooperativity, obtaining evidence for significant cooperativity (1.0-2.5 kcal/mol) when simultaneously forming two adjacent Hoogsteen base pairs. We also measured the thermodynamic preferences to form G-C+ and A-T Hoogsteen and A-T base open states for nearly all sixteen trinucleotide sequence contexts and found distinct sequence-specific variations on the order of 2-3 kcal/mol. This rich landscape of sequence-specific non-native minor conformations in the DNA double helix may help shape the sequence-specificity of DNA biochemistry. Thus, melting experiments can now be used to access thermodynamic information regarding regions of the free energy landscape of biomolecules beyond the native folded and unfolded conformations. Significance StatementThermodynamic preferences of nucleic acids to adopt non-native conformations are crucial for understanding how they function but prove difficult to measure experimentally. As a result, little is known about how these thermodynamic preferences vary with sequence and structural contexts, physiological conditions, and chemical modifications. Here, we show that modifications stabilizing non-native conformations and rendering them the major state, in conjunction with melting experiments, enable facile measurements of thermodynamic preferences to form various non-native conformations in DNA and RNA. delta-melt provided rare insights into the cooperativity of forming tandem Hoogsteen base pairs and revealed large and distinct sequence-specific preferences to form G-C+ and A-T Hoogsteen and A-T base open conformations in DNA, which may contribute to sequence-specific DNA biochemistry.

biophysics↗

bioRxiv2020

A quantitative model predicts how m6A reshapes the kinetic landscape of nucleic acid hybridization and conformational transitions

N6-methyladenosine (m6A) is a post-transcriptional modification that controls gene expression by recruiting proteins to RNA sites. The modification also slows biochemical processes through mechanisms that are not understood. Using NMR relaxation dispersion, we show that m6A pairs with uridine with the methylamino group in the anti conformation to form a Watson-Crick base pair that transiently exchanges on the millisecond timescale with a singly hydrogen-bonded low-populated (1%) mismatch-like conformation in which the methylamino group is syn. This ability to rapidly interchange between Watson-Crick or mismatch-like forms, combined with different syn:anti isomer preferences when paired (~1:100) versus unpaired (~10:1), explains how m6A robustly slows duplex annealing without affecting melting via two pathways in which isomerization occurs before or after duplex annealing. Our model quantitatively predicts how m6A reshapes the kinetic landscape of nucleic acid hybridization and conformational transitions, and provides an explanation for why the modification robustly slows diverse cellular processes.

biochemistry↗

bioRxiv2020

Starvation induces shrinkage of the bacterial cytoplasm

Environmental fluctuations are a common challenge for single-celled organisms; enteric bacteria such as Escherichia coli experience dramatic changes in nutrient availability, pH, and temperature during their journey into and out of the host. While the effects of altered nutrient availability on gene expression and protein synthesis are well known, their impacts on cytoplasmic dynamics and cell morphology have been largely overlooked. Here, we discover that depletion of utilizable nutrients results in shrinkage of E. colis inner membrane from the cell wall. Shrinkage was accompanied by a [~]17% reduction in cytoplasmic volume and a concurrent increase in periplasmic volume. Inner membrane retraction occurred almost exclusively at the new cell pole. This phenomenon was distinct from turgor-mediated plasmolysis and independent of new transcription, translation, or canonical starvation-sensing pathways. Cytoplasmic dry-mass density increased during shrinkage, suggesting that it is driven primarily by loss of water. Shrinkage was reversible: upon a shift to nutrient-rich medium, expansion started almost immediately at a rate dependent on carbon-source quality. Robust recovery from starvation required the Tol-Pal system, highlighting the importance of envelope coupling during recovery. Klebsiella pneumoniae also exhibited shrinkage when shifted to carbon-free conditions, suggesting a conserved phenomenon. These findings demonstrate that even when Gram-negative bacterial growth is arrested, cell morphology and physiology are still dynamic. Significance statementBacterial cells constantly face nutrient fluctuations in their natural environments. While previous studies have identified gene expression changes upon nutrient depletion, it is much less well known how cellular morphology and cytoplasmic properties respond to shifts in nutrient availability. Here, we discovered that switching fast-growing Escherichia coli cells to nutrient-free conditions results in substantial shrinkage of the inner membrane away from the cell wall, especially at the new pole. Shrinkage was primarily driven by loss of cytoplasmic water contents. Shrinkage was also exhibited by cells naturally entering stationary phase, highlighting its biological relevance across starvation conditions. The membrane-spanning Tol-Pal system was critical for robust entry into and recovery from shrinkage, indicating the importance of cell-envelope homeostasis in surviving nutrient starvation.

microbiology↗

bioRxiv2020

3D Genome Contributes to Protein-Protein Interactome

Numerous computational methods have been proposed to predict protein-protein interactions, none of which however, considers the original DNA loci of the interacting proteins in the perspective of 3D genome. Here we retrospect the DNA origins of the interacting proteins in the context of 3D genome and discovered that 1) if a gene pair is more proximate in 3D genome, their corresponding proteins are more likely to interact. 2) signal peptide involvement of PPI affects the corresponding gene-gene proximity in 3D genome space. 3) by incorporating 3D genome information, existing PPI prediction methods can be further improved in terms of accuracy. Combining our previous discoveries, we conjecture the existence of 3D genome driven cellular compartmentalization, meaning the co-localization of DNA elements lead to increased probability of the co-localization of RNA elements and protein elements.

bioinformatics↗

bioRxiv2020

Candidate Explorer: a tool for discovery, evaluation, and display of mutations causing significant immune phenotypes

When applied to immunity, forward genetic studies use meiotic mapping to provide strong statistical evidence that a particular mutation is causative of a particular immune phenotype. Notwithstanding this, co-segregation of multiple mutations, occasional unawareness of mutations, and paucity of homozygotes may lead to erroneous declarations of cause and effect. We sought to improve the selection of authentic causative mutations using a machine learning software tool, Candidate Explorer (CE), which integrates 65 data features into a single numeric score, mathematically convertible to the likelihood of verification of any putative mutation-phenotype association. CE has identified most genes within which mutations can be causative of flow cytometric phenovariation in Mus musculus. The majority of these genes were not previously known to support immune function or homeostasis. Mouse geneticists will find CE data informative in identifying causative mutations within quantitative trait loci, while clinical geneticists may use CE to help connect causative variants with rare heritable diseases of immunity, even in the absence of linkage information. CE displays integrated mutation, phenotype, and linkage data, and is freely available for query online.

genetics↗

bioRxiv2020

Information-theory-based benchmarking and feature selection algorithm improve cell type annotation and reproducibility of single cell RNA-seq data analysis pipelines

Single cell RNA sequencing (scRNA-seq) data are now routinely generated in experimental practice because of their promise to enable the quantitative study of biological processes at the single cell level. However, cell type and cell state annotations remain an important computational challenge in analyzing scRNA-seq data. Here, we report on the development of a benchmark dataset where reference annotations are generated independently from transcriptomic measurements. We used this benchmark to systematically investigate the impact on labelling accuracy of different approaches to feature selection, of different clustering algorithms, and of different sets of parameter values. We show that an approach grounded on information theory can provide a general, reliable, and accurate process for discarding uninformative features and to optimize cluster resolution in single cell RNA-seq data analysis.

bioinformatics↗

bioRxiv2020

Mechanism of negative regulation of NF-κB by N4BP1

Many immune responses depend upon activation of NF-{kappa}B, a key transcription factor in the elicitation of a cytokine response. Here we demonstrate that N4BP1 inhibited TLR-dependent activation of NF-{kappa}B by interacting with the NF-{kappa}B signaling essential modulator (NEMO, also known as I{kappa}B kinase {gamma}) to attenuate NEMO-NEMO dimerization or oligomerization. The UBA-like (ubiquitin associated-like) and CUE-like (ubiquitin conjugation to ER degradation) domains in N4BP1 mediated the interaction with the NEMO COZI domain. Both in vitro and in mice, N4bp1 deficiency specifically enhanced TRIF-independent (TLR2, TLR7, or TLR9-mediated), but not TRIF-dependent (TLR3 or TLR4-mediated), NF-{kappa}B activation leading to increased production of proinflammatory cytokines. In response to TLR4 or TLR3 activation, TRIF caused activation of caspase 8, which cleaved N4BP1 distal to residues D424 and D490 and abolished its inhibitory effect. N4bp1-/- mice also exhibited diminished numbers of T cells in the peripheral blood. Our work identifies N4BP1 as an inhibitory checkpoint protein that must be overcome to activate NF-{kappa}B, and a TRIF-initiated caspase 8-dependent mechanism by which this is accomplished.

immunology↗

bioRxiv2020

Negative short-range genomic autocorrelation of causal effects on human complex traits

Most models of complex trait genetic architecture assume that signed causal effect sizes of each SNP (defined with respect to the minor allele) are uncorrelated with those of nearby SNPs, but it is currently unknown whether this is the case. We develop a new method, autocorrelation LD regression (ACLR), for estimating the genome-wide autocorrelation of causal minor allele effect sizes as a function of genomic distance. Our method estimates these autocorrelations by regressing the products of summary statistics on distance-dependent LD scores. We determined that ACLR robustly assesses the presence or absence of nonzero autocorrelation, producing unbiased estimates with well-calibrated standard errors in null simulations regardless of genetic architecture; if true autocorrelation is nonzero, ACLR correctly detects its sign, although estimates of the autocorrelation magnitude are susceptible to bias in cases of certain genetic architectures. We applied ACLR to 31 diseases and complex traits from the UK Biobank (average N=331K), meta-analyzing results across traits. We determined that autocorrelations were significantly negative at distances of 1-50bp (P = 8 x 10-6, point estimate -0.35 {+/-}0.08) and 50-100bp (P = 2 x 10-3, point estimate -0.33 {+/-} 0.11). We show that the autocorrelation is primarily driven by pairs of SNPs in positive LD, which is consistent with the expectation that linked SNPs with opposite effects are less impacted by natural selection. Our findings suggest that this mechanism broadly affects complex trait genetic architectures, and we discuss implications for association mapping, heritability estimation, and genetic risk prediction.

genetics↗

bioRxiv2020

Comparative analysis reveals the species-specific genetic determinants of ACE2 required for SARS-CoV-2 entry

Coronavirus interaction with its viral receptor is a primary genetic determinant of host range and tissue tropism. SARS-CoV-2 utilizes ACE2 as the receptor to enter host cell in a species-specific manner. We and others have previously shown that ACE2 orthologs from New World monkey, koala and mouse cannot interact with SARS-CoV-2 to mediate viral entry, and this defect can be restored by humanization of the restrictive residues in New World monkey ACE2. To better understand the genetic determinants behind the ability of ACE2 orthologs to support viral entry, we compared koala and mouse ACE2 sequences with that of human and identified the key residues in koala and mouse ACE2 that restrict viral receptor activity. Humanization of these critical residues rendered both koala and mouse ACE2 capable of binding the spike protein and facilitating viral entry. The single mutation that allowed for mouse ACE2 to serve as a viral receptor provides a potential avenue for the development of SARS-CoV-2 mouse model.

microbiology↗

bioRxiv2020

Single-cell analysis identifies TCF4 and ID3 as a molecular switch of mammary epithelial stem cell differentiation.

It is well known that the expansion of the mammary epithelium during the ovarian cycles in female mammals is supported by the transient increase in mammary epithelial stem cells (MaSCs). However, dissecting the molecular mechanisms that govern MaSC function and differentiation is poorly understood due to the lack of standardized methods for their identification and isolation. The development of robust single-cell mRNA sequencing () technologies and the computational methods to analyze them provides us with novel tools to approach the challenge of studying MaSCs in a completely unbiased way without. Here, we have performed the largest scRNA-seq analysis of individual mammary epithelial cells (~70,000 cells). Our study identified a distinct cell population presenting molecular features of MaSCs. Importantly, further purification and additional in-depth single-cell analysis of these cells revealed that they are not a fully homogenous entity. Instead, we identified three subpopulations representing early stages of lineage commitment. By tracking their molecular evolution through single-cell network analysis we found that one of these subpopulations represents bipotent MaSCs from which luminal and basal lineages diverge. Importantly, we also confirmed the presence of these cells in human mammary glands. Finally, through expression and network analysis studies, we have uncovered transcription factors that are activated early during lineage commitment. These data identified E2-2 (Tcf4) and ID3 as a potential molecular switch of mammary epithelial stem cell differentiation.

developmental biology↗

bioRxiv2020

DNN-DTIs: improved drug-target interactions prediction using XGBoost feature selection and deep neural network

Research, analysis, and prediction of drug-target interactions (DTIs) play an important role in understanding drug mechanisms, drug repositioning and design. Machine learning (ML)-based methods for DTIs prediction can mitigate the shortcomings of time-consuming and labor-intensive experimental approaches, providing new ideas and insights for drug design. We propose a novel pipeline for predicting drug-target interactions, called DNN-DTIs. First, the target information is characterized by pseudo-amino acid composition, pseudo position-specific scoring matrix, conjoint triad, composition, transition and distribution, Moreau-Broto autocorrelation, and structure feature. Then, the drug compounds are encoded using substructure fingerprint. Next, we utilize XGBoost to determine nonredundant and important feature subset, then the optimized and balanced sample vectors could be obtained through SMOTE. Finally, a DTIs predictor, DNN-DTIs, is developed based on deep neural network (DNN) via layer-by-layer learning. Experimental results indicate that DNN-DTIs achieves outstanding performance than other predictors with the ACC values of 98.78%, 98.60%, 97.98%, 98.24% and 98.00% on Enzyme, Ion Channels (IC), GPCR, Nuclear Receptors (NR) and Kuang's dataset. Therefore, DNN-DTIs's accurate prediction performance on Network1 and Network2 make it logical choice for contributing to the study of DTIs, especially, the drug repositioning and new usage of old drugs.

bioinformatics↗

bioRxiv2020

The inner membrane protein YhdP modulates the rate of anterograde phospholipid flow in Escherichia coli

The outer membrane (OM) of Gram-negative bacteria is a selective permeability barrier that allows uptake of nutrients while simultaneously protecting the cell from harmful compounds. The basic pathways and molecular machinery responsible for transporting lipopolysaccharides (LPS), lipoproteins, and {beta}-barrel proteins to the OM have been identified, but very little is known about phospholipid (PL) transport. To identify genes capable of affecting PL transport, we screened for genetic interactions with mlaA*, a mutant in which anterograde PL transport causes the inner membrane (IM) to shrink and eventually rupture; characterization of mlaA*-mediated lysis suggested that PL transport can occur via a high-flux, diffusive flow mechanism. We found that YhdP, an IM protein involved in maintaining the OM permeability barrier, modulates the rate of PL transport during mlaA*-mediated lysis. Deletion of yhdP from mlaA* reduced the rate of IM transport to the OM by 50%, slowing shrinkage of the IM and delaying lysis. As a result, the weakened OM of {Delta}ydhP cells was further compromised and ruptured before the IM during mlaA*-mediated death. These findings demonstrate the existence of a high-flux, diffusive pathway for PL flow in Escherichia coli that is modulated by YhdP. Significance StatementThe outer membrane (OM) of Gram-negative bacteria serves as a barrier that protects cells from harmful chemical compounds, including many antibiotics. Understanding how bacteria build this barrier is an important step in engineering strategies to circumvent it. A long-standing mystery in the field is how phospholipids (PLs) are transported from the inner membrane (IM) to the OM. We previously discovered that a mutation in the gene mlaA causes rapid flow of PLs to the OM, eventually resulting in IM rupture. Here, we found that deletion of the gene yhdP delayed cell death in the mlaA mutant by slowing flow of PLs to the OM. These findings reveal a high-flux, diffusive pathway for PL transport in Gram-negative bacteria modulated by YhdP.

molecular biology↗

bioRxiv2020

Epigenetic Interaction between UTX and DNMT1 Regulates Diet-Induced Myogenic Remodeling in Brown Fat

Brown adipocytes share the same developmental origin with skeletal muscle. Here we find that a brown adipocyte-to-myocyte remodeling also exists in mature brown adipocytes, and is induced by prolonged high fat diet (HFD) feeding, leading to brown fat dysfunction. This process is regulated by the interaction of epigenetic pathways involving histone and DNA methylation. In mature brown adipocytes, the histone demethylase UTX maintains persistent demethylation of the repressive mark H3K27me3 at Prdm16 promoter, leading to high Prdm16 expression. PRDM16 then recruits DNA methyltransferase DNMT1 to Myod1 promoter, causing Myod1 promoter hypermethylation and suppressing its expression. The interaction between PRDM16 and DNMT1 coordinately serves to maintain brown adipocyte identity while repressing myogenic remodeling in mature brown adipocytes, thus promoting their active brown adipocyte thermogenic function. Suppressing this interaction by HFD feeding induces brown adipocyte-to-myocyte remodeling, which limits brown adipocyte thermogenic capacity and compromises diet-induced thermogenesis, leading to the development of obesity.

physiology↗

bioRxiv2020

Retinoic acid rewires the adrenergic core regulatory circuitry of neuroblastoma but can be subverted by enhancer hijacking of MYC or MYCN

Neuroblastoma cell identity depends on a core regulatory circuit (CRC) of transcription factors that collaborate with MYCN to drive the oncogenic gene expression program. For neuroblastomas dependent on the adrenergic CRC, treatment with retinoids can inhibit cell growth and induce differentiation. Here we show that when MYCN-amplified neuroblastomas cells are treated with retinoic acid, histone H3K27 acetylation and methylation become redistributed to decommission super-enhancers driving the expression of PHOX2B and GATA3, together with the activation of new super-enhancers that drive high levels of MEIS1 and SOX4 expression. These findings indicate that treatment with retinoids can reprogram the enhancer landscape, resulting in downregulation of MYCN expression, while establishing a new retino-sympathetic CRC that causes proliferative arrest and sympathetic differentiation. Thus, we provide mechanisms that account for the beneficial effects of retinoids in high-risk neuroblastoma and explain the rapid downregulation of expression of MYCN despite massive levels of amplification of this gene.

cancer biology↗

bioRxiv2020

Individual cell-based modeling of tumor cell plasticity-induced immune escape after CAR-T therapy

Chimeric antigen receptor (CAR) therapy targeting CD19 is an effective treatment for refractory B cell malignancies, especially B cell acute lymphoblastic leukemia (B-ALL). The majority of patients achieve a complete response following a single infusion of CD19-targeted CAR-modified T cells (CAR-19 T cells); however, many patients suffer relapse after therapy, and the underlying mechanism remains unclear. To better understand the mechanism of tumor relapse, we developed an individual cell based computational model for tumor cell plasticity and the heterogeneous responses to the CAR-T treatment. Model simulations reproduced the process of tumor relapse, and predicted that CAR-T stress-induced cell plasticity can lead to tumor relapse in B-ALL. Model predictions were verified by applying the second-generation CAR-T cells to mice injected with NALM-6-GL leukemic cells, in which 60% of the mice relapse within 3 months, and relapsed tumors retained CD19 expression but exhibited a subpopulation of cells with CD34 transcription. These findings lead to a mechanism of tumor replace by which CAR-T treatment induced tumor cells to transition to hematopoietic stem-like cells (HSLCs) and myeloid-like cells and hence escape of CAR-T targeting. The computational model framework was successfully developed to recapitulate the individual evolutionary dynamics, which could predict clinical survival outcomes in B-ALL patients after CAR-T therapy.

cancer biology↗

bioRxiv2020

Environmental and physiological factors affecting high-throughput measurements of bacterial growth

Bacterial growth in nutrient-rich and starvation conditions is intrinsically tied to the environmental history and physiological state of the population. While high-throughput technologies have enabled rapid analyses of mutant libraries, technical and biological challenges complicate data collection and interpretation. Here, we present a framework for the execution and analysis of growth measurements with improved accuracy over standard approaches. Using this framework, we demonstrate key biological insights that emerge from consideration of culturing conditions and history. We determined that quantification of the background absorbance in each well of a multi-well plate is critical for accurate measurements of maximal growth rate. Using mathematical modeling, we demonstrated that maximal growth rate is dependent on initial cell density, which distorts comparisons across strains with variable lag properties. We established a multiple-passage protocol that alleviates the substantial effects of glycerol on growth in carbon-poor media, and we tracked growth rate-mediated fitness increases observed during a long-term evolution of Escherichia coli in low glucose concentrations. Finally, we showed that growth of Bacillus subtilis in the presence of glycerol induces a long lag in the next passage due to inhibition of a large fraction of the population. Transposon mutagenesis linked this phenotype to the incorporation of glycerol into lipoteichoic acids, revealing a new role for these envelope components in resuming growth after starvation. Together, our investigations underscore the complex physiology of bacteria during bulk passaging and the importance of robust strategies to understand and quantify growth. Abstract ImportanceHow starved bacteria adapt to and multiply in replete nutrient conditions is intimately linked to their history of previous growth, their physiological state, and the surrounding environment. While automated equipment has enabled high-throughput growth measurements, data interpretation and knowledge gaps regarding the determinants of growth kinetics complicate comparisons between strains. Here, we present a framework for growth measurements that improves accuracy and attenuates the effects of growth history. We determined that background absorbance quantification and multiple passaging cycles allows for accurate growth-rate measurements even in carbon-poor media, which we used to reveal growth-rate increases during long-term laboratory evolution of Escherichia coli. Using mathematical modeling, we showed that maximum growth rate depends on initial cell density. Finally, we demonstrated that growth of Bacillus subtilis with glycerol inhibits the future growth of most of the population, due to lipoteichoic-acid synthesis. These studies highlight the challenges of accurate quantification of bacterial growth behaviors.

microbiology↗