Some exciting biological questions require quantifying thousands of proteins in single cells. To achieve this goal, we develop Single Cell ProtEomics by Mass Spectrometry (SCoPE-MS) and validate its ability to identify distinct human cancer cell types based on their proteomes. We use SCoPE-MS to quantify over a thousand proteins in differentiating mouse embryonic stem cells. The single-cell proteomes enable us to deconstruct cell populations and infer protein abundance relationships. Comparison between single-cell proteomes and transcriptomes indicates coordinated mRNA and protein covariation, yet many genes exhibit functionally concerted and distinct regulatory patterns at the mRNA and the protein level.Electronic supplementary materialThe online version of this article (10.1186/s13059-018-1547-5) contains supplementary material, which is available to authorized users.

Neuropathological studies, using a variety of techniques, have reported a decrease in Purkinje cell (PC) density in the cerebellum in autism. We have used a systematic sampling technique that significantly reduces experimenter bias and variance to estimate PC densities in the postmortem brains of eight clinically well-documented individuals with autism, and eight age- and gender-matched controls. Four cerebellar regions were analyzed: a sensorimotor area comprised of hemispheric lobules IV–VI, crus I & II of the posterior lobe, and lobule X of the flocculonodular lobe. Overall PC density was thus estimated using data from all three cerebellar lobes and was found to be lower in the cases with autism as compared to controls, an effect that was most prominent in crus I and II (p<0.05). Lobule X demonstrated a trend towards lower PC density in only the males with autism (p = 0.05). Brain weight, a correlate of tissue volume, was found to significantly contribute to the lower lobule X PC density observed in males with autism, but not to the finding of lower PC density in crus I & II. Therefore, lower crus I & II PC density in autism is more likely due to a lower number of PCs. The PC density in lobule X was found to correlate with the ADI-R measure of the patient's use of social eye contact (R2 = −0.75, p = 0.012). These findings support the hypothesis that abnormal PC density may contribute to selected clinical features of the autism phenotype.

Cellular heterogeneity is important to biological processes, including cancer and development. However, proteome heterogeneity is largely unexplored because of the limitations of existing methods for quantifying protein levels in single cells. To alleviate these limitations, we developed Single Cell ProtEomics by Mass Spectrometry (SCoPE-MS), and validated its ability to identify distinct human cancer cell types based on their proteomes. We used SCoPE-MS to quantify over a thousand proteins in differentiating mouse embryonic stem (ES) cells. The single-cell proteomes enabled us to deconstruct cell populations and infer protein abundance relationships. Comparison between single-cell proteomes and transcriptomes indicated coordinated mRNA and protein covariation. Yet many genes exhibited functionally concerted and distinct regulatory patterns at the mRNA and the protein levels, suggesting that post-transcriptional regulatory mechanisms contribute to proteome remodeling during lineage specification, especially for developmental genes. SCoPE-MS is broadly applicable to measuring proteome configurations of single cells and linking them to functional phenotypes, such as cell type and differentiation potentials.. CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under a The copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/102681 doi: bioRxiv preprint first posted online Cellular systems, such as tissues, cancers, and cell cultures, consist of a variety of cells with distinct molecular and functional properties. Characterizing such cellular differences is key to understanding normal physiology, combating cancer recurrence (1, 2), and enhancing targeted differentiation for regenerative therapies (3); it demands quantifying the proteomes of single cells. To overcome the second challenge, we made novel use of tandem mass tags (TMT). This technology was developed for multiplexing (12), which affords cost-effective high-throughput.Even more crucial to our application, TMT allows quantifying the level of each TMT-labeled 2 . CC-BY-NC-ND 4.0 International license peer-reviewed) is the author/funder. It is made available under aThe copyright holder for this preprint (which was not . http://dx.doi.org/10.1101/102681 doi: bioRxiv preprint first posted online Jan. 24, 2017; peptide in each sample while identifying its sequence from the total peptide amount pooled across all samples (12). SCoPE-MS capitalizes on this capability by augmenting each single-cell set with a sample comprised of ∼ 100 − 200 carrier cells that provide enough ions for peptide sequence identification, Fig. 1a. Increasing the number of carrier cells increases peptide identification rates but decreases quantitative precision. The carrier cells also help with the first challenge by reducing losses from single cells, since most of the peptides sticking to tips and tube walls originate from the carrier cells. Thus, the carrier cells help overcome the two major challenges.Quantificat...

The cellular abundance of proteins can vary even between isogenic single cells. This variability between single-cell protein levels can have regulatory roles, such as controlling cell fate during apoptosis induction or the proliferation/quiescence decision. Here, we review examples connecting protein levels and their dynamics in single cells to cellular functions. Such findings were made possible by the introduction of antibodies, and subsequently fluorescent proteins, for tracking protein levels in single cells. However, in heterogeneous cell populations, such as tumors or differentiating stem cells, cellular decisions are controlled by hundreds, even thousands of proteins acting in concert. Characterizing such complex systems demands measurements of thousands of proteins across thousands of single cells. This demand has inspired the development of new methods for single-cell protein analysis, and we discuss their trade-offs, with an emphasis on their specificity and coverage. We finish by highlighting the potential of emerging mass-spec methods to enable systems-level measurement of single-cell proteomes with unprecedented coverage and specificity. Combining such methods with methods for quantitating the transcriptomes and metabolomes of single cells will provide essential data for advancing quantitative systems biology.

Individuals with spinal cord injury have a shortened life expectancy, with coronary heart disease as a leading cause of death. Identifying potentially reversible risk factors would be expected to be of value in the long-term care of the person with a spinal cord injury. We addressed the relationships among diet, body mass index, and serum lipid levels in 28 veterans with paraplegia compared to 52 age-matched ambulatory veteran controls. There are no significant differences in body mass index or in total caloric, saturated fat, or cholesterol intake between those with paraplegia and the control group. The serum HDL cholesterol level is significantly lower in those with paraplegia compared to the control group (35 +/- 2 vs 49 +/- 2 mg/dL). There are no significant differences noted in serum total cholesterol, LDL cholesterol, or triglycerides between the groups. Total caloric intake decreases significantly with age in the control subjects but not in the subjects with paraplegia. Inverse correlations are found between serum HDL cholesterol and serum triglycerides levels both in those with paraplegia (r = -0.54, p less than 0.005) and in the controls (r = -0.42, p less than 0.001). In our group of subjects with paraplegia, serum lipid levels appear to be independent of dietary intake and body weight.

Unanticipated D2 cooking loss from fresh UVB mushrooms and probable low absorption and/or hydroxylation may explain the smaller increase in 25OHD2 in our prediabetic overweight/obese cohort compared with past findings in younger, healthy subjects. Moreover, no dose or vitamin D source was associated with modifying T2D risk factors.

The urea cycle functions to incorporate ammonia, generated by normal metabolism, into urea. Urea cycle disorders (UCDs) are caused by loss of function in any of the enzymes responsible for ureagenesis, and are characterized by life-threatening episodes of acute metabolic decompensation with hyperammonemia (HA). A prospective analysis of interim HA events in a cohort of individuals with ornithine transcarbamylase (OTC) deficiency, the most common UCD, revealed that intercurrent infection was the most common precipitant of acute HA and was associated with markers of increased morbidity when compared with other precipitants. To further understand these clinical observations, we developed a model system of metabolic decompensation with HA triggered by viral infection (PR8 influenza) using spf-ash mice, a model of OTC deficiency. Both wild-type (WT) and spf-ash mice displayed similar cytokine profiles and lung viral titers in response to PR8 influenza infection. During infection, spf-ash mice displayed an increase in liver transaminases, suggesting a hepatic sensitivity to the inflammatory response and an altered hepatic immune response. Despite having no visible pathological changes by histology, WT and spf-ash mice had reduced CPS1 and OTC enzyme activities, and, unlike WT, spf-ash mice failed to increase ureagenesis. Depression of urea cycle function was seen in liver amino acid analysis, with reductions seen in aspartate, ornithine and arginine during infection. In conclusion, we developed a model system of acute metabolic decompensation due to infection in a mouse model of a UCD. In addition, we have identified metabolic perturbations during infection in the spf-ash mice, including a reduction of urea cycle intermediates. This model of acute metabolic decompensation with HA due to infection in UCD serves as a platform for exploring biochemical perturbations and the efficacy of treatments, and could be adapted to explore acute decompensation in other types of inborn errors of metabolism.

The cellular abundance of proteins can vary even between isogenic single cells. This variability between single-cell protein levels can have functional roles, such as controlling cell fate during apoptosis induction or the proliferation/quiescence decision. Here, we review such examples of connecting protein levels and their dynamics in single cells to cellular functions. Such findings were made possible by the introduction of antibodies, and subsequently fluorescent proteins, for tracking protein levels in single cells. However, in heterogeneous cell populations, such as tumors or differentiating stem cells, cellular decisions are controlled by hundreds, even thousands of proteins acting in concert. Characterizing such complex systems demands measurements of thousands of proteins across thousands of single cells. This demand has inspired the development of new methods for single cell protein analysis, and we discuss their trade-offs, with emphasis on their specificity and coverage. We finish by highlighting the potential of emerging mass-spec methods to enable systems-level measurement of single-cell proteomes with unprecedented coverage and specificity. Combining such methods with methods for quantifying the trasncriptomes and metabolomes of single cells will provide essential data for advancing quantitative systems biology.