An Improved Boosting to Amplify Signal with Isobaric Labeling (iBASIL) Strategy for Precise Quantitative Single-cell Proteomics.

Mass spectrometry (MS)-based proteomics has great potential for overcoming the limitations of antibody-based immunoassays for antibody-independent, comprehensive, and quantitative proteomic analysis of single cells. Indeed, recent advances in nanoscale sample preparation have enabled effective processing of single cells. In particular, the concept of using boosting/carrier channels in isobaric labeling to increase the sensitivity in MS detection has also been increasingly used for quantitative proteomic analysis of small-sized samples including single cells. However, the full potential of such boosting/carrier approaches has not been significantly explored, nor has the resulting quantitation quality been carefully evaluated. Herein, we have further evaluated and optimized our recent boosting to amplify signal with isobaric labeling (BASIL) approach, originally developed for quantifying phosphorylation in small number of cells, for highly effective analysis of proteins in single cells. This improved BASIL (iBASIL) approach enables reliable quantitative single-cell proteomics analysis with greater proteome coverage by carefully controlling the boosting-to-sample ratio (e.g. in general <100×) and optimizing MS automatic gain control (AGC) and ion injection time settings in MS/MS analysis (e.g. 5E5 and 300 ms, respectively, which is significantly higher than that used in typical bulk analysis). By coupling with a nanodroplet-based single cell preparation (nanoPOTS) platform, iBASIL enabled identification of ∼2500 proteins and precise quantification of ∼1500 proteins in the analysis of 104 FACS-isolated single cells, with the resulting protein profiles robustly clustering the cells from three different acute myeloid leukemia cell lines. This study highlights the importance of carefully evaluating and optimizing the boosting ratios and MS data acquisition conditions for achieving robust, comprehensive proteomic analysis of single cells.

Comprehensive Detection of Single Amino Acid Variants and Evaluation of Their Deleterious Potential in a PANC-1 Cell Line.

Identifying single amino acid variants (SAAVs) in cancer is critical for precision oncology. Several advanced algorithms are now available to identify SAAVs, but attempts to combine different algorithms and optimize them on large data sets to achieve a more comprehensive coverage of SAAVs have not been implemented. Herein, we report an expanded detection of SAAVs in the PANC-1 cell line using three different strategies, which results in the identification of 540 SAAVs in the mass spectrometry data. Among the set of 540 SAAVs, 79 are evaluated as deleterious SAAVs based on analysis using the novel AssVar software in which one of the driver mutations found in each protein of KRAS, TP53, and SLC37A4 is further validated using independent selected reaction monitoring (SRM) analysis. Our study represents the most comprehensive discovery of SAAVs to date and the first large-scale detection of deleterious SAAVs in the PANC-1 cell line. This work may serve as the basis for future research in pancreatic cancer and personal immunotherapy and treatment.

Three-dimensional shoulder complex kinematics in individuals with upper extremity impairment from chronic stroke.

PURPOSE: To evaluate shoulder complex kinematics in persons with chronic upper extremity (UE) impairments due to stroke and determine if kinematics predicts motor function based on the Fugl-Meyer Motor Assessment (FMA). METHODS: Sixteen stroke survivors with chronic UE impairments (age range = 46-80 years, male = 8, female = 8, mean (SD) 66 (40) months post-stroke) performed the UE portion of the FMA with the shoulder/elbow subscale (FM_se) documented. Three-dimensional kinematics of the shoulder complex was collected with the Motion Monitor™ (Innsport, Chicago, IL, USA). Participants performed three repetitions of arm elevation in the frontal, sagittal and self-selected planes. The third repetition was analyzed. Scapular and humeral kinematics were calculated in the self-selected plane. Scapulohumeral rhythm was analyzed at peak elevation. Backward stepwise regression analysis predicted kinematic contributions to the FM_se. RESULTS: Mean (SD) FM_se score was 25.3 1(10.9). Peak humeral elevation ranged from 45.6° to 129.2° (median 106.7°). Scapulohumeral rhythm was 4.1:1 when humeral elevation ranged from 45° to 50°, 1.5:1 from 80° to 95° and 2.1:1 from 105° to 130°. Humeral elevation, scapular upward rotation and scapular internal rotation predicted 65.4% of FM_se score variability. CONCLUSIONS: Persons with chronic UE impairments from stroke demonstrated reduced peak elevation and altered scapulohumeral rhythm. Three predictors of the FM_se were humeral elevation, scapular upward rotation and scapular internal rotation.