Tradeoffs in bacterial physiology determine the efficiency of antibiotic killing.

Antibiotic effectiveness depends on a variety of factors. While many mechanistic details of antibiotic action are known, the connection between death rate and bacterial physiology is poorly understood. A common observation is that death rate in antibiotics rises linearly with growth rate; however, it remains unclear how other factors, such as environmental conditions and whole-cell physiological properties, affect bactericidal activity. To address this, we developed a high-throughput assay to precisely measure antibiotic-mediated death. We found that death rate is linear in growth rate, but the slope depends on environmental conditions. Growth under stress lowers death rate compared to nonstressed environments with similar growth rate. To understand stress's role, we developed a mathematical model of bacterial death based on resource allocation that includes a stress-response sector; we identify this sector using RNA-seq. Our model accurately predicts the minimal inhibitory concentration (MIC) with zero free parameters across a wide range of growth conditions. The model also quantitatively predicts death and MIC when sectors are experimentally modulated using cyclic adenosine monophosphate (cAMP), including protection from death at very low cAMP levels. The present study shows that different conditions with equal growth rate can have different death rates and establishes a quantitative relation between growth, death, and MIC that suggests approaches to improve antibiotic efficacy.

The tumor microenvironment shows a hierarchy of cell-cell interactions dominated by fibroblasts.

The tumor microenvironment (TME) is comprised of non-malignant cells that interact with each other and with cancer cells, critically impacting cancer biology. The TME is complex, and understanding it requires simplifying approaches. Here we provide an experimental-mathematical approach to decompose the TME into small circuits of interacting cell types. We find, using female breast cancer single-cell-RNA-sequencing data, a hierarchical network of interactions, with cancer-associated fibroblasts (CAFs) at the top secreting factors primarily to tumor-associated macrophages (TAMs). This network is composed of repeating circuit motifs. We isolate the strongest two-cell circuit motif by culturing fibroblasts and macrophages in-vitro, and analyze their dynamics and transcriptomes. This isolated circuit recapitulates the hierarchy of in-vivo interactions, and enables testing the effect of ligand-receptor interactions on cell dynamics and function, as we demonstrate by identifying a mediator of CAF-TAM interactions - RARRES2, and its receptor CMKLR1. Thus, the complexity of the TME may be simplified by identifying small circuits, facilitating the development of strategies to modulate the TME.

Autoimmune thyroid diseases as a cost of physiological autoimmune surveillance.

Graves' disease (GD) and Hashimoto's thyroiditis (HT) are common autoimmune diseases of the thyroid gland, causing hyperthyroidism and hypothyroidism, respectively. Despite their opposing clinical manifestation, they have several enigmatic links. Here, we propose that GD and HT have the same fundamental origin: both diseases are the cost of a beneficial physiological process called autoimmune surveillance of hypersecreting mutants. Autoreactive T cells selectively eliminate mutant cells that hypersecrete the hormones and threaten to become toxic nodules. These T cells can trigger a humoral response in susceptible individuals, leading to the production of antibodies against thyroid antigens. This shared origin can explain similarities in incidence and risk factors between HT and GD, despite their opposite clinical phenotypes.

Prostanoid receptors in hyperfiltration-mediated glomerular injury: Novel agonists and antagonists reveal opposing roles for EP2 and EP4 receptors.

Increased fluid-flow shear stress (FFSS) contributes to hyperfiltration-induced podocyte and glomerular injury resulting in progression of chronic kidney disease (CKD). We reported that increased FFSS in vitro and in vivo upregulates PGE2 receptor EP2 (but not EP4 expression), COX2-PGE2 -EP2 axis, and EP2-linked Akt-GSK3ß-ß-catenin signaling pathway in podocytes. To understand and use the disparities between PGE2 receptors, specific agonists, and antagonists of EP2 and EP4 were used to assess phosphorylation of Akt, GSK3ß and ß-catenin in podocytes using Western blotting, glomerular filtration barrier function using in vitro albumin permeability (Palb ) assay, and mitigation of hyperfiltration-induced injury in unilaterally nephrectomized (UNX) mice at 1 and 6 months. Results show an increase in Palb by PGE2 , EP2 agonist (EP2AGO ) and EP4 antagonist (EP4ANT ), but not by EP2 antagonist (EP2ANT ) or EP4 agonist (EP4AGO ). Pretreatment with EP2ANT blocked the effect of PGE2 or EP2AGO on Palb . Modulation of EP2 and EP4 also induced opposite effects on phosphorylation of Akt and ß-Catenin. Individual agonists or antagonists of EP2 or EP4 did not induce significant improvement in albuminuria in UNX mice. However, treatment with a combination EP2ANT + EP4AGO for 1 or 6 months caused a robust decrease in albuminuria. EP2ANT + EP4AGO combination did not impact adaptive hypertrophy or increased serum creatinine. Observed differences between expression of EP2 and EP4 on the glomerular barrier highlight these receptors as potential targets for intervention. Safe and effective mitigating effect of EP2ANT + EP4AGO presents a novel opportunity to delay the progression of hyperfiltration-associated CKD as seen in transplant donors.

A Mechanism for Ovulation Number Control.

Every menstrual cycle, many follicles begin to develop but only a specific number ovulate. This ovulation number determines how many offspring are produced per litter, and differs between species. The physiological mechanism that controls ovulation number is unknown; a class of mathematical models can explain it, but these models have no physiological basis. Here, we suggest a physiological mechanism for ovulation number control, which enables selection of a specific number of follicles out of many, and analyze it in a mathematical model of follicular growth. The mechanism is based on a signal, intra-follicular androgen concentration, that measures follicle size relative to the other follicles. This signal has a biphasic effect, suppressing follicles that are too large or too small compared to others. The ovulation number is determined by the androgen inhibitory thresholds. The model has a scaling symmetry that explains why the dominant follicles grow linearly with time, as observed in human ultrasound data. This approach also explains how chronic hyperandrogenism disrupts ovulation in polycystic ovary syndrome (PCOS), a leading cause of infertility. We propose specific experiments for testing the proposed mechanism.

Controls for Phylogeny and Robust Analysis in Pareto Task Inference.

Understanding the tradeoffs faced by organisms is a major goal of evolutionary biology. One of the main approaches for identifying these tradeoffs is Pareto task inference (ParTI). Two recent papers claim that results obtained in ParTI studies are spurious due to phylogenetic dependence (Mikami T, Iwasaki W. 2021. The flipping t-ratio test: phylogenetically informed assessment of the Pareto theory for phenotypic evolution. Methods Ecol Evol. 12(4):696-706) or hypothetical p-hacking and population-structure concerns (Sun M, Zhang J. 2021. Rampant false detection of adaptive phenotypic optimization by ParTI-based Pareto front inference. Mol Biol Evol. 38(4):1653-1664). Here, we show that these claims are baseless. We present a new method to control for phylogenetic dependence, called SibSwap, and show that published ParTI inference is robust to phylogenetic dependence. We show how researchers avoided p-hacking by testing for the robustness of preprocessing choices. We also provide new methods to control for population structure and detail the experimental tests of ParTI in systems ranging from ammonites to cancer gene expression. The methods presented here may help to improve future ParTI studies.

Single cell biology-a Keystone Symposia report.

Single cell biology has the potential to elucidate many critical biological processes and diseases, from development and regeneration to cancer. Single cell analyses are uncovering the molecular diversity of cells, revealing a clearer picture of the variation among and between different cell types. New techniques are beginning to unravel how differences in cell state-transcriptional, epigenetic, and other characteristics-can lead to different cell fates among genetically identical cells, which underlies complex processes such as embryonic development, drug resistance, response to injury, and cellular reprogramming. Single cell technologies also pose significant challenges relating to processing and analyzing vast amounts of data collected. To realize the potential of single cell technologies, new computational approaches are needed. On March 17-19, 2021, experts in single cell biology met virtually for the Keystone eSymposium "Single Cell Biology" to discuss advances both in single cell applications and technologies.

A mouse model of prenatal exposure to Interleukin-6 to study the developmental origin of health and disease.

Systemic inflammation in pregnant obese women is associated with 1.5- to 2-fold increase in serum Interleukin-6 (IL-6) and newborns with lower kidney/body weight ratio but the role of IL-6 in increased susceptibility to chronic kidney (CKD) in adult progeny is not known. Since IL-6 crosses the placental barrier, we administered recombinant IL-6 (10 pg/g) to pregnant mice starting at mid-gestation yielded newborns with lower body (p < 0.001) and kidney (p < 0.001) weights. Histomorphometry indicated decreased nephrogenic zone width (p = 0.039) with increased numbers of mature glomeruli (p = 0.002) and pre-tubular aggregates (p = 0.041). Accelerated maturation in IL-6 newborns was suggested by early expression of podocyte-specific protein podocin in glomeruli, increased 5-methyl-cytosine (LC-MS analysis for CpG DNA methylation) and altered expression of certain genes of cell-cycle and apoptosis (RT-qPCR array-analysis). Western blotting showed upregulated pJAK2/pSTAT3. Thus, treating dams with IL-6 as a surrogate provides newborns to study effects of maternal systemic inflammation on future susceptibility to CKD in adulthood.

Transcription Factor ß-Catenin Plays a Key Role in Fluid Flow Shear Stress-Mediated Glomerular Injury in Solitary Kidney.

Increased fluid flow shear stress (FFSS) in solitary kidney alters podocyte function in vivo. FFSS-treated cultured podocytes show upregulated AKT-GSK3ß-ß-catenin signaling. The present study was undertaken to confirm (i) the activation of ß-catenin signaling in podocytes in vivo using unilaterally nephrectomized (UNX) TOPGAL mice with the ß-galactosidase reporter gene for ß-catenin activation, (ii) ß-catenin translocation in FFSS-treated mouse podocytes, and (iii) ß-catenin signaling using publicly available data from UNX mice. The UNX of TOPGAL mice resulted in glomerular hypertrophy and increased the mesangial matrix consistent with hemodynamic adaptation. Uninephrectomized TOPGAL mice showed an increased ß-galactosidase expression at 4 weeks but not at 12 weeks, as assessed using immunofluorescence microscopy (p < 0.001 at 4 weeks; p = 0.16 at 12 weeks) and X-gal staining (p = 0.008 at 4 weeks; p = 0.65 at 12 weeks). Immunofluorescence microscopy showed a significant increase in phospho-ß-catenin (Ser552, p = 0.005) at 4 weeks but not at 12 weeks (p = 0.935) following UNX, and the levels of phospho-ß-catenin (Ser675) did not change. In vitro FFSS caused a sustained increase in the nuclear translocation of phospho-ß-catenin (Ser552) but not phospho-ß-catenin (Ser675) in podocytes. The bioinformatic analysis of the GEO dataset, #GSE53996, also identified ß-catenin as a key upstream regulator. We conclude that transcription factor ß-catenin mediates FFSS-induced podocyte (glomerular) injury in solitary kidney.

Senescent cells and the incidence of age-related diseases.

Age-related diseases such as cancer, cardiovascular disease, kidney failure, and osteoarthritis have universal features: Their incidence rises exponentially with age with a slope of 6-8% per year and decreases at very old ages. There is no conceptual model which explains these features in so many diverse diseases in terms of a single shared biological factor. Here, we develop such a model, and test it using a nationwide medical record dataset on the incidence of nearly 1000 diseases over 50 million life-years, which we provide as a resource. The model explains incidence using the accumulation of senescent cells, damaged cells that cause inflammation and reduce regeneration, whose level rise stochastically with age. The exponential rise and late drop in incidence are captured by two parameters for each disease: the susceptible fraction of the population and the threshold concentration of senescent cells that causes disease onset. We propose a physiological mechanism for the threshold concentration for several disease classes, including an etiology for diseases of unknown origin such as idiopathic pulmonary fibrosis and osteoarthritis. The model can be used to design optimal treatments that remove senescent cells, suggeting that treatment starting at old age can sharply reduce the incidence of all age-related diseases, and thus increase the healthspan.

Upregulated proteoglycan-related signaling pathways in fluid flow shear stress-treated podocytes.

The ultrafiltrate flow over the major processes and cell body generates fluid flow shear stress (FFSS) on podocytes. Hyperfiltration-associated increase in FFSS can lead to podocyte injury and detachment. Previously, we showed that FFSS-induced upregulation of the cyclooxygenase 2 (COX2)-PGE2-prostaglandin E receptor 2 (EP2) axis in podocytes activates Akt-glycogen synthase kinase-3ß-ß-catenin and MAPK/ERK signaling in response to FFSS. Integrative MultiOmics Pathway Resolution (IMPRes) is a new bioinformatic tool that enables simultaneous time-series analysis of more than two groups to identify pathways and molecular connections. In the present study, we used previously characterized COX2 [prostaglandin-endoperoxide synthase 2 (Ptgs2)], EP2 (Ptger2), and ß1-catenin (Ctnnb1) as "seed genes" from an array data set of four groups analyzed over a time course. The 3 seed genes shared 7 pathways and 50 genes of 14 pathways and 89 genes identified by IMPRes. A composite of signaling pathways highlighted the temporal molecular connections during mechanotransduction signaling in FFSS-treated podocytes. We investigated the "proteoglycans in cancer" and "galactose metabolism" pathways predicted by IMPRes. A custom-designed PCR array validated 60.7% of the genes predicted by IMPRes analysis, including genes for the above-named pathways. Further validation using Western blot analysis showed increased expression of phosho-Erbb2, phospho-mammalian target of rapamycin (mTOR), CD44, and hexokinase II (Hk2); decreased total Erbb2, galactose mutarotase (Galm), and ß-1,4-galactosyltransferase 1 (B4galt1); and unchanged total mTOR and AKT3. These findings corroborate our previously reported results. This study demonstrates the potential of the IMPRes method to identify novel pathways. Identifying the "proteoglycans in cancer" and "galactose metabolism" pathways has generated a lead to study the significance of FFSS-induced glycocalyx remodeling and possible detachment of podocytes from the glomerular matrix.

Endocrine Autoimmune Disease as a Fragility of Immune Surveillance against Hypersecreting Mutants.

Some endocrine organs are frequent targets of autoimmune attack. Here, we addressed the origin of autoimmune disease from the viewpoint of feedback control. Endocrine tissues maintain mass through feedback loops that balance cell proliferation and removal according to hormone-driven regulatory signals. We hypothesized the existence of a dedicated mechanism that detects and removes mutant cells that missense the signal and therefore hyperproliferate and hypersecrete with potential to disrupt organismal homeostasis. In this mechanism, hypersecreting cells are preferentially eliminated by autoreactive T cells at the cost of a fragility to autoimmune disease. The "autoimmune surveillance of hypersecreting mutants" (ASHM) hypothesis predicts the presence of autoreactive T cells in healthy individuals and the nature of self-antigens as peptides from hormone secretion pathway. It explains why some tissues get prevalent autoimmune disease, whereas others do not and instead show prevalent mutant-expansion disease (e.g., hyperparathyroidism). The ASHM hypothesis is testable, and we discuss experimental follow-up.

Tumour heterogeneity and the evolutionary trade-offs of cancer.

Tumours vary in gene expression programmes and genetic alterations. Understanding this diversity and its biological meaning requires a theoretical framework, which could in turn guide the development of more accurate prognosis and therapy. Here, we review the theory of multi-task evolution of cancer, which is based upon the premise that tumours evolve in the host and face selection trade-offs between multiple biological functions. This theory can help identify the major biological tasks that cancer cells perform and the trade-offs between these tasks. It introduces the concept of specialist tumours, which focus on one task, and generalist tumours, which perform several tasks. Specialist tumours are suggested to be sensitive to therapy targeting their main task. Driver mutations tune gene expression towards specific tasks in a tissue-dependent manner and thus help to determine whether a tumour is specialist or generalist. We discuss potential applications of the theory of multi-task evolution to interpret the spatial organization of tumours and intratumour heterogeneity.

Cancer-associated fibroblast compositions change with breast cancer progression linking the ratio of S100A4+ and PDPN+ CAFs to clinical outcome.

Tumors are supported by cancer-associated fibroblasts (CAFs). CAFs are heterogeneous and carry out distinct cancer-associated functions. Understanding the full repertoire of CAFs and their dynamic changes as tumors evolve could improve the precision of cancer treatment. Here we comprehensively analyze CAFs using index and transcriptional single-cell sorting at several time points along breast tumor progression in mice, uncovering distinct subpopulations. Notably, the transcriptional programs of these subpopulations change over time and in metastases, transitioning from an immunoregulatory program to wound-healing and antigen-presentation programs, indicating that CAFs and their functions are dynamic. Two main CAF subpopulations are also found in human breast tumors, where their ratio is associated with disease outcome across subtypes and is particularly correlated with BRCA mutations in triple-negative breast cancer. These findings indicate that the repertoire of CAF changes over time in breast cancer progression, with direct clinical implications.

Tumor diversity and the trade-off between universal cancer tasks.

Recent advances have enabled powerful methods to sort tumors into prognosis and treatment groups. We are still missing, however, a general theoretical framework to understand the vast diversity of tumor gene expression and mutations. Here we present a framework based on multi-task evolution theory, using the fact that tumors need to perform multiple tasks that contribute to their fitness. We find that trade-offs between tasks constrain tumor gene-expression to a continuum bounded by a polyhedron whose vertices are gene-expression profiles, each specializing in one task. We find five universal cancer tasks across tissue-types: cell-division, biomass and energy, lipogenesis, immune-interaction and invasion and tissue-remodeling. Tumors that specialize in a task are sensitive to drugs that interfere with this task. Driver, but not passenger, mutations tune gene-expression towards specialization in specific tasks. This approach can integrate additional types of molecular data into a framework of tumor diversity grounded in evolutionary theory.

Prediction of ultra-high-order antibiotic combinations based on pairwise interactions.

Drug combinations are a promising approach to achieve high efficacy at low doses and to overcome resistance. Drug combinations are especially useful when drugs cannot achieve effectiveness at tolerable doses, as occurs in cancer and tuberculosis (TB). However, discovery of effective drug combinations faces the challenge of combinatorial explosion, in which the number of possible combinations increases exponentially with the number of drugs and doses. A recent advance, called the dose model, uses a mathematical formula to overcome combinatorial explosion by reducing the problem to a feasible quadratic one: using data on drug pairs at a few doses, the dose model accurately predicts the effect of combinations of three and four drugs at all doses. The dose model has not yet been tested on higher-order combinations beyond four drugs. To address this, we measured the effect of combinations of up to ten antibiotics on E. coli growth, and of up to five tuberculosis (TB) drugs on the growth of M. tuberculosis. We find that the dose model accurately predicts the effect of these higher-order combinations, including cases of strong synergy and antagonism. This study supports the view that the interactions between drug pairs carries key information that largely determines higher-order interactions. Therefore, systematic study of pairwise drug interactions is a compelling strategy to prioritize drug regimens in high-dimensional spaces.

Successful Brace Treatment of Pectus Carinatum in Osteogenesis Imperfecta Using the Dynamic Compression System.

Osteogenesis imperfecta (OI) is a genetic disorder of collagen resulting in a "fragile" skeleton with increased fracture risk and other complications, dependent on the specific variant. Pectus deformities of the chest wall, while not common, can be associated with OI. The use of a pectus carinatum brace in a patient with OI poses unknown risks for fractures and adverse treatment outcomes. We successfully applied external compression bracing using the dynamic compression system to one such patient. This case illustrates the ability to treat an OI patient with pectus carinatum using a nonsurgical brace, without complications, resulting in an excellent cosmetic result.

Circuit Design Features of a Stable Two-Cell System.

Cell communication within tissues is mediated by multiple paracrine signals including growth factors, which control cell survival and proliferation. Cells and the growth factors they produce and receive constitute a circuit with specific properties that ensure homeostasis. Here, we used computational and experimental approaches to characterize the features of cell circuits based on growth factor exchange between macrophages and fibroblasts, two cell types found in most mammalian tissues. We found that the macrophage-fibroblast cell circuit is stable and robust to perturbations. Analytical screening of all possible two-cell circuit topologies revealed the circuit features sufficient for stability, including environmental constraint and negative-feedback regulation. Moreover, we found that cell-cell contact is essential for the stability of the macrophage-fibroblast circuit. These findings illustrate principles of cell circuit design and provide a quantitative perspective on cell interactions.

Successful Reversal of Furosemide-Induced Secondary Hyperparathyroidism With Cinacalcet.

Secondary hyperparathyroidism (SHPT) is a rare complication of furosemide therapy that can occur in patients treated with the loop diuretic for a long period of time. We report a 6-month-old 28-weeks premature infant treated chronically with furosemide for his bronchopulmonary dysplasia, who developed hypocalcemia and severe SHPT, adversely affecting his bones. Discontinuation of the loop diuretic and the addition of supplemental calcium and calcitriol only partially reversed the SHPT, bringing serum parathyroid hormone level down from 553 to 238 pg/mL. After introduction of the calcimimetic Cinacalcet, we observed a sustained normalization of parathyroid hormone concentration at 27 to 63 pg/mL and, with that correction, of all biochemical abnormalities and healing of the bone disease. No adverse effects were noted. We conclude that in cases of SHPT due to furosemide in which traditional treatment fails, there may be room to consider the addition of a calcimimetic agent.

Dynamic Proteomics of Herpes Simplex Virus Infection.

The cellular response to viral infection is usually studied at the level of cell populations. Currently, it remains an open question whether and to what extent cell-to-cell variability impacts the course of infection. Here we address this by dynamic proteomics-imaging and tracking 400 yellow fluorescent protein (YFP)-tagged host proteins in individual cells infected by herpes simplex virus 1. By quantifying time-lapse fluorescence imaging, we analyze how cell-to-cell variability impacts gene expression from the viral genome. We identify two proteins, RFX7 and geminin, whose levels at the time of infection correlate with successful initiation of gene expression. These proteins are cell cycle markers, and we find that the position in the cell cycle at the time of infection (along with the cell motility and local cell density) can reasonably predict in which individual cells gene expression from the viral genome will commence. We find that the onset of cell division dramatically impacts the progress of infection, with 70% of dividing cells showing no additional gene expression after mitosis. Last, we identify four host proteins that are specifically modulated in infected cells, of which only one has been previously recognized. SUMO2 and RPAP3 levels are rapidly reduced, while SLTM and YTHDC1 are redistributed to form nuclear foci. These modulations are dependent on the expression of ICP0, as shown by infection with two mutant viruses that lack ICP0. Taken together, our results provide experimental validation for the long-held notion that the success of infection is dependent on the state of the host cell at the time of infection.IMPORTANCE High-throughput assays have revolutionized many fields in biology, both by allowing a more global understanding of biological processes and by deciphering rare events in subpopulations. Here we use such an assay, dynamic proteomics, to study viral infection at the single-cell level. We follow tens of thousands of individual cells infected by herpes simplex virus using fluorescence live imaging. Our results link the state of a cell at the time of virus infection with its probability to successfully initiate gene expression from the viral genome. Further, we identified three cellular proteins that were previously unknown to respond to viral infection. We conclude that dynamic proteomics provides a powerful tool to study single-cell differences during viral infection.