Neural Unbalanced Optimal Transport via Cycle-Consistent Semi-Couplings

Comparing unpaired samples of a distribution or population taken at different points in time is a fundamental task in many application domains where measuring populations is destructive and cannot be done repeatedly on the same sample, such as in single-cell biology. Optimal transport (OT) can solve this challenge by learning an optimal coupling of samples across distributions from unpaired data. However, the usual formulation of OT assumes conservation of mass, which is violated in unbalanced scenarios in which the population size changes (e.g., cell proliferation or death) between measurements. In this work, we introduce NubOT, a neural unbalanced OT formulation that relies on the formalism of semi-couplings to account for creation and destruction of mass. To estimate such semi-couplings and generalize out-of-sample, we derive an efficient parameterization based on neural optimal transport maps and propose a novel algorithmic scheme through a cycle-consistent training procedure. We apply our method to the challenging task of forecasting heterogeneous responses of multiple cancer cell lines to various drugs, where we observe that by accurately modeling cell proliferation and death, our method yields notable improvements over previous neural optimal transport methods

Characterization of the neurogenic niche in the aging dentate gyrus using iterative immunofluorescence imaging

Advancing age causes reduced hippocampal neurogenesis, associated with age-related cognitive decline. The spatial relationship of age-induced alterations in neural stem cells (NSCs) and surrounding cells within the hippocampal niche remains poorly understood due to limitations of antibody-based cellular phenotyping. We established iterative indirect immunofluorescence imaging (4i) in tissue sections, allowing for simultaneous detection of 18 proteins to characterize NSCs and surrounding cells in 2-, 6-, and 12-month-old mice. We show that reorganization of the dentate gyrus (DG) niche already occurs in middle-aged mice, paralleling the decline in neurogenesis. 4i-based tissue analysis of the DG identifies changes in cell-type contributions to the blood-brain barrier and microenvironments surrounding NSCs to play a pivotal role to preserve neurogenic permissiveness. The data provided represent a resource to characterize the principles causing alterations of stem cell-associated plasticity within the aging DG and provide a blueprint to analyze somatic stem cell niches across lifespan in complex tissues

SUCLA2 mutations cause global protein succinylation contributing to the pathomechanism of a hereditary mitochondrial disease

Mitochondrial acyl-coenzyme A species are emerging as important sources of protein modification and damage. Succinyl-CoA ligase (SCL) deficiency causes a mitochondrial encephalomyopathy of unknown pathomechanism. Here, we show that succinyl-CoA accumulates in cells derived from patients with recessive mutations in the tricarboxylic acid cycle (TCA) gene succinyl-CoA ligase subunit-beta (SUCLA2), causing global protein hyper-succinylation. Using mass spectrometry, we quantify nearly 1,000 protein succinylation sites on 366 proteins from patient-derived fibroblasts and myotubes. Interestingly, hyper-succinylated proteins are distributed across cellular compartments, and many are known targets of the (NAD(+))-dependent desuccinylase SIRT5. To test the contribution of hyper-succinylation to disease progression, we develop a zebrafish model of the SCL deficiency and find that SIRT5 gain-of-function reduces global protein succinylation and improves survival. Thus, increased succinyl-CoA levels contribute to the pathology of SCL deficiency through post-translational modifications. The pathomechanism of succinyl-CoA ligase (SCL) deficiency, a hereditary mitochondrial disease, is not fully understood. Here, the authors show that increased succinyl-CoA levels contribute to SCL pathology by causing global protein hyper-succinylation.Peer reviewe

Prevalence and incidence of iron deficiency in European community-dwelling older adults : An observational analysis of the DO-HEALTH trial

Background and aim Iron deficiency is associated with increased morbidity and mortality in older adults. However, data on its prevalence and incidence among older adults is limited. The aim of this study was to investigate the prevalence and incidence of iron deficiency in European community-dwelling older adults aged ≥ 70 years. Methods Secondary analysis of the DO-HEALTH trial, a 3-year clinical trial including 2157 community-dwelling adults aged ≥ 70 years from Austria, France, Germany, Portugal and Switzerland. Iron deficiency was defined as soluble transferrin receptor (sTfR) > 28.1 nmol/L. Prevalence and incidence rate (IR) of iron deficiency per 100 person-years were examined overall and stratified by sex, age group, and country. Sensitivity analysis for three commonly used definitions of iron deficiency (ferritin  1.5) were also performed. Results Out of 2157 participants, 2141 had sTfR measured at baseline (mean age 74.9 years; 61.5% women). The prevalence of iron deficiency at baseline was 26.8%, and did not differ by sex, but by age (35.6% in age group ≥ 80, 29.3% in age group 75–79, 23.2% in age group 70–74); P  1.5. Occurrences of iron deficiency were observed with IR per 100 person-years of 9.2 (95% CI 8.3–10.1) and did not significantly differ by sex or age group. The highest IR per 100 person-years was observed in Austria (20.8, 95% CI 16.1–26.9), the lowest in Germany (6.1, 95% CI 4.7–8.0). Regarding the other definitions of iron deficiency, the IR per 100 person-years was 4.5 (95% CI 4.0–4.9) for ferritin  1.5. Conclusions Iron deficiency is frequent among relatively healthy European older adults, with people aged ≥ 80 years and residence in Austria and Portugal associated with the highest risk

Multiplexed protein maps link subcellular organization to cellular state

Being able to visualize protein localizations within cells and tissues by means of immuno-fluorescence microscopy has been key to developments in cell biology and beyond. Gut et al. present a high-throughput method that achieves the detection of more than 40 different proteins in biological samples across multiple spatial scales. This allows the simultaneous quantification of their expression levels in thousands of single cells; captures their detailed subcellular distribution to various compartments, organelles, and cellular structures within each of these single cells; and places all this information within a multicellular context. Such a scale-crossing dataset empowers artificial intelligence–based computer vision algorithms to achieve a comprehensive profiling of intracellular protein maps to measure their responses to different multicellular, cellular, and pharmacological contexts, and to reveal new cellular states

Dealing with Headache: Sex Differences in the Burden of Migraine- and Tension-Type Headache

OBJECTIVE The aim of this study was to investigate sex differences in the burden of migraine and tension-type headache (TTH). BACKGROUND Migraine and TTH are more common in women than in men, with differences in comorbidities, treatment responses, disease-modifying factors, and ictal and interictal burden of disease. Information about sex-related influences on ictal and interictal burden is limited, and an increased understanding is mandatory to provide tailored individual treatment for female and male patients. METHODS Participants answered an online survey based on the EUROLIGHT questionnaire. Inclusion criteria were the consent to participate, complete responses to the diagnostic questions, and information about their sex. Sex differences were investigated using the Mann-Whitney U test or Chi-square test. For detecting factors that influence the burden of disease, we built binary regression models. RESULTS We included 472 (74.6% female) migraineurs and 161 (59.6% female) participants with TTH. Women with migraine reported significantly more problems in their love lives, more self-concealment, less feelings of being understood by family and friends, more interictal anxiety, a higher pain severity, and more depression and anxiety symptoms than men. For TTH, we did not find significant sex-related differences. A higher headache frequency was the factor that increased the burden of disease in female but not in male migraneurs. CONCLUSION The burden of disease was higher in women than men with migraine in many aspects, but not with TTH. Therefore, according to our results, there is a need for sex-specific precision medicine for migraine but not TTH. Controlling the headache frequency with a proper acute or prophylactic treatment and treating comorbid depression and anxiety symptoms is crucial to ease migraine's burden, especially in women

Learning Single-Cell Perturbation Responses using Neural Optimal Transport

The ability to understand and predict molecular responses towards external perturbations is a core question in molecular biology. Technological advancements in the recent past have enabled the generation of high-resolution single-cell data, making it possible to profile individual cells under different experimentally controlled perturbations. However, cells are typically destroyed during measurement, resulting in unpaired distributions over either perturbed or non-perturbed cells. Leveraging the theory of optimal transport and the recent advents of convex neural architectures, we learn a coupling describing the response of cell populations upon perturbation, enabling us to predict state trajectories on a single-cell level. We apply our approach, CellOT, to predict treatment responses of 21,650 cells subject to four different drug perturbations. CellOT outperforms current state-of-the-art methods both qualitatively and quantitatively, accurately capturing cellular behavior shifts across all different drugs.Competing Interest StatementG.G. and L.P. have filed a patent on the 4i technology (patentWO2019207004A1)

Learning single-cell perturbation responses using neural optimal transport

Understanding and predicting molecular responses in single cells upon chemical, genetic or mechanical perturbations is a core question in biology. Obtaining single-cell measurements typically requires the cells to be destroyed. This makes learning heterogeneous perturbation responses challenging as we only observe unpaired distributions of perturbed or non-perturbed cells. Here we leverage the theory of optimal transport and the recent advent of input convex neural architectures to present CellOT, a framework for learning the response of individual cells to a given perturbation by mapping these unpaired distributions. CellOT outperforms current methods at predicting single-cell drug responses, as profiled by scRNA-seq and a multiplexed protein-imaging technology. Further, we illustrate that CellOT generalizes well on unseen settings by (1) predicting the scRNA-seq responses of holdout patients with lupus exposed to interferon-beta and patients with glioblastoma to panobinostat; (2) inferring lipopolysaccharide responses across different species; and (3) modeling the hematopoietic developmental trajectories of different subpopulations.ISSN:1548-7105ISSN:1548-709