TDP-43-stratified single-cell proteomics of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis.

A limitation of conventional bulk-tissue proteome studies in amyotrophic lateral sclerosis (ALS) is the confounding of motor neuron (MN) signals by admixed non-MN proteins. Here, we leverage laser capture microdissection and nanoPOTS single-cell mass spectrometry-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control tissues. In a follow-up analysis, we examine the impact of stratification of MNs based on cytoplasmic transactive response DNA-binding protein 43 (TDP-43)+ inclusion pathology on the profiles of 2,238 proteins. We report extensive overlap in differentially abundant proteins identified in ALS MNs with or without overt TDP-43 pathology, suggesting early and sustained dysregulation of cellular respiration, mRNA splicing, translation, and vesicular transport in ALS. Together, these data provide insights into proteome-level changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein dynamics in human neurologic diseases.

A novel method for quantitation of AAV genome integrity using duplex digital PCR.

Recombinant adeno-associated virus (rAAV) vectors have become a reliable strategy for delivering gene therapies. As rAAV capsid content is known to be heterogeneous, methods for rAAV characterization are critical for assessing the efficacy and safety of drug products. Multiplex digital PCR (dPCR) has emerged as a popular molecular approach for characterizing capsid content due to its high level of throughput, accuracy, and replicability. Despite growing popularity, tools to accurately analyze multiplexed data are scarce. Here, we introduce a novel statistical model to estimate genome integrity from duplex dPCR assays. This work demonstrates that use of a Poisson-multinomial mixture distribution significantly improves the accuracy and quantifiable range of duplex dPCR assays over currently available models.

TDP-43-stratified single-cell proteomic profiling of postmortem human spinal motor neurons reveals protein dynamics in amyotrophic lateral sclerosis.

Unbiased proteomics has been employed to interrogate central nervous system (CNS) tissues (brain, spinal cord) and fluid matrices (CSF, plasma) from amyotrophic lateral sclerosis (ALS) patients; yet, a limitation of conventional bulk tissue studies is that motor neuron (MN) proteome signals may be confounded by admixed non-MN proteins. Recent advances in trace sample proteomics have enabled quantitative protein abundance datasets from single human MNs (Cong et al., 2020b). In this study, we leveraged laser capture microdissection (LCM) and nanoPOTS (Zhu et al., 2018c) single-cell mass spectrometry (MS)-based proteomics to query changes in protein expression in single MNs from postmortem ALS and control donor spinal cord tissues, leading to the identification of 2515 proteins across MNs samples (>900 per single MN) and quantitative comparison of 1870 proteins between disease groups. Furthermore, we studied the impact of enriching/stratifying MN proteome samples based on the presence and extent of immunoreactive, cytoplasmic TDP-43 inclusions, allowing identification of 3368 proteins across MNs samples and profiling of 2238 proteins across TDP-43 strata. We found extensive overlap in differential protein abundance profiles between MNs with or without obvious TDP-43 cytoplasmic inclusions that together point to early and sustained dysregulation of oxidative phosphorylation, mRNA splicing and translation, and retromer-mediated vesicular transport in ALS. Our data are the first unbiased quantification of single MN protein abundance changes associated with TDP-43 proteinopathy and begin to demonstrate the utility of pathology-stratified trace sample proteomics for understanding single-cell protein abundance changes in human neurologic diseases.

Independent study demonstrates amyloid probability score accurately indicates amyloid pathology.

BACKGROUND: The amyloid probability score (APS) is the model read-out of the analytically validated mass spectrometry-based PrecivityAD® blood test that incorporates the plasma Aß42/40 ratio, ApoE proteotype, and age to identify the likelihood of brain amyloid plaques among cognitively impaired individuals being evaluated for Alzheimer's disease. PURPOSE: This study aimed to provide additional independent evidence that the pre-established APS algorithm, along with its cutoff values, discriminates between amyloid positive and negative individuals. METHODS: The diagnostic performance of the PrecivityAD test was analyzed in a cohort of 200 nonrandomly selected Australian Imaging, Biomarker & Lifestyle Flagship Study of Aging (AIBL) study participants, who were either cognitively impaired or healthy controls, and for whom a blood sample and amyloid PET imaging were available. RESULTS: In a subset of the dataset aligned with the Intended Use population (patients aged 60 and older with CDR ≥0.5), the pre-established APS algorithm predicted amyloid PET with a sensitivity of 84.9% (CI: 72.9-92.1%) and specificity of 96% (CI: 80.5-99.3%), exclusive of 13 individuals for whom the test was inconclusive. INTERPRETATION: The study shows individuals with a high APS are more likely than those with a low APS to have abnormal amounts of amyloid plaques and be on an amyloid accumulation trajectory, a dynamic and evolving process characteristic of progressive AD pathology. Exploratory data suggest APS retains its diagnostic performance in healthy individuals, supporting further screening studies in the cognitively unimpaired.

Recommendations of scRNA-seq Differential Gene Expression Analysis Based on Comprehensive Benchmarking.

To guide analysts to select the right tool and parameters in differential gene expression analyses of single-cell RNA sequencing (scRNA-seq) data, we developed a novel simulator that recapitulates the data characteristics of real scRNA-seq datasets while accounting for all the relevant sources of variation in a multi-subject, multi-condition scRNA-seq experiment: the cell-to-cell variation within a subject, the variation across subjects, the variability across cell types, the mean/variance relationship of gene expression across genes, library size effects, group effects, and covariate effects. By applying it to benchmark 12 differential gene expression analysis methods (including cell-level and pseudo-bulk methods) on simulated multi-condition, multi-subject data of the 10x Genomics platform, we demonstrated that methods originating from the negative binomial mixed model such as glmmTMB and NEBULA-HL outperformed other methods. Utilizing NEBULA-HL in a statistical analysis pipeline for single-cell analysis will enable scientists to better understand the cell-type-specific transcriptomic response to disease or treatment effects and to discover new drug targets. Further, application to two real datasets showed the outperformance of our differential expression (DE) pipeline, with unified findings of differentially expressed genes (DEG) and a pseudo-time trajectory transcriptomic result. In the end, we made recommendations for filtering strategies of cells and genes based on simulation results to achieve optimal experimental goals.

Cell-autonomous and non-cell autonomous effects of neuronal BIN1 loss in vivo.

BIN1 is the most important risk locus for Late Onset Alzheimer's Disease (LOAD), after ApoE. BIN1 AD-associated SNPs correlate with Tau deposition as well as with brain atrophy. Furthermore, the level of neuronal-specific BIN1 isoform 1 protein is decreased in sporadic AD cases in parallel with neuronal loss, despite an overall increase in BIN1 total mRNA. To address the relationship between reduction of BIN1 and neuronal cell loss in the context of Tau pathology, we knocked-down endogenous murine Bin1 via stereotaxic injection of AAV-Bin1 shRNA in the hippocampus of mice expressing Tau P301S (PS19). We observed a statistically significant reduction in the number of neurons in the hippocampus of mice injected with AAV-Bin1 shRNA in comparison with mice injected with AAV control. To investigate whether neuronal loss is due to deletion of Bin1 selectively in neurons in presence Tau P301S, we bred Bin1flox/flox with Thy1-Cre and subsequently with PS19 mice. Mice lacking neuronal Bin1 and expressing Tau P301S showed increased mortality, without increased neuropathology, when compared to neuronal Bin1 and Tau P301S-expressing mice. The loss of Bin1 isoform 1 resulted in reduced excitability in primary neurons in vitro, reduced neuronal c-fos expression as well as in altered microglia transcriptome in vivo. Taken together, our data suggest that the contribution of genetic variation in BIN1 locus to AD risk could result from a cell-autonomous reduction of neuronal excitability due to Bin1 decrease, exacerbated by the presence of aggregated Tau, coupled with a non-cell autonomous microglia activation.