Intercellular communication within the virus microenvironment affects the susceptibility of cells to secondary viral infections.

Communication between infected cells and cells in the surrounding tissue is a determinant of viral spread. However, it remains unclear how cells in close or distant proximity to an infected cell respond to primary or secondary infections. We establish a cell-based system to characterize a virus microenvironment, distinguishing infected, neighboring, and distal cells. Cell sorting, microscopy, proteomics, and cell cycle assays allow resolving cellular features and functional consequences of proximity to infection. We show that human cytomegalovirus (HCMV) infection primes neighboring cells for both subsequent HCMV infections and secondary infections with herpes simplex virus 1 and influenza A. Neighboring cells exhibit mitotic arrest, dampened innate immunity, and altered extracellular matrix. Conversely, distal cells are poised to slow viral spread due to enhanced antiviral responses. These findings demonstrate how infection reshapes the microenvironment through intercellular signaling to facilitate spread and how spatial proximity to an infection guides cell fate.

Capillary Electrophoresis Coupled to Electrospray Ionization Tandem Mass Spectrometry for Ultra-Sensitive Proteomic Analysis of Limited Samples.

In this work, we developed an ultra-sensitive CE-MS/MS method for bottom-up proteomics analysis of limited samples, down to sub-nanogram levels of total protein. Analysis of 880 and 88 pg of the HeLa protein digest standard by CE-MS/MS yielded ∼1100 ± 46 and ∼160 ± 59 proteins, respectively, demonstrating higher protein and peptide identifications than the current state-of-the-art CE-MS/MS-based proteomic analyses with similar amounts of sample. To demonstrate potential applications of our ultra-sensitive CE-MS/MS method for the analysis of limited biological samples, we digested 500 and 1000 HeLa cells using a miniaturized in-solution digestion workflow. From 1-, 5-, and 10-cell equivalents injected from the resulted digests, we identified 744 ± 127, 1139 ± 24, and 1271 ± 6 proteins and 3353 ± 719, 5709 ± 513, and 8527 ± 114 peptide groups, respectively. Furthermore, we performed a comparative assessment of CE-MS/MS and two reversed-phased nano-liquid chromatography (RP-nLC-MS/MS) methods (monolithic and packed columns) for the analysis of a ∼10 ng HeLa protein digest standard. Our results demonstrate complementarity in the protein- and especially peptide-level identifications of the evaluated CE-MS- and RP-nLC-MS-based methods. The techniques were further assessed to detect post-translational modifications and highlight the strengths of the CE-MS/MS approach in identifying potentially important and biologically relevant modified peptides. With a migration window of ∼60 min, CE-MS/MS identified ∼2000 ± 53 proteins on average from a single injection of ∼8.8 ng of the HeLa protein digest standard. Additionally, an average of 232 ± 10 phosphopeptides and 377 ± 14 N-terminal acetylated peptides were identified in CE-MS/MS analyses at this sample amount, corresponding to 2- and 1.5-fold more identifications for each respective modification found by nLC-MS/MS methods.

Simple and Efficient Microsolid-Phase Extraction Tip-Based Sample Preparation Workflow to Enable Sensitive Proteomic Profiling of Limited Samples (200 to 10,000 Cells).

In-depth LC-MS-based proteomic profiling of limited biological and clinical samples, such as rare cells or tissue sections from laser capture microdissection or microneedle biopsies, has been problematic due, in large, to the inefficiency of sample preparation and attendant sample losses. To address this issue, we developed on-microsolid-phase extraction tip (OmSET)-based sample preparation for limited biological samples. OmSET is simple, efficient, reproducible, and scalable and is a widely accessible method for processing ∼200 to 10,000 cells. The developed method benefits from minimal sample processing volumes (1-3 µL) and conducting all sample processing steps on-membrane within a single microreactor. We first assessed the feasibility of using micro-SPE tips for nanogram-level amounts of tryptic peptides, minimized the number of required sample handling steps, and reduced the hands-on time. We then evaluated the capability of OmSET for quantitative analysis of low numbers of human monocytes. Reliable and reproducible label-free quantitation results were obtained with excellent correlations between protein abundances and the amounts of starting material (R2 = 0.93) and pairwise correlations between sample processing replicates (R2 = 0.95) along with the identification of approximately 300, 1800, and 2000 protein groups from injected ∼10, 100, and 500 cell equivalents, resulting from processing approximately 200, 2000, and 10,000 cells, respectively.

Improved Sensitivity of Ultralow Flow LC-MS-Based Proteomic Profiling of Limited Samples Using Monolithic Capillary Columns and FAIMS Technology.

In this work, we pioneered a combination of ultralow flow (ULF) high-efficiency ultranarrow bore monolithic LC columns coupled to MS via a high-field asymmetric waveform ion mobility spectrometry (FAIMS) interface to evaluate the potential applicability for high sensitivity, robust, and reproducible proteomic profiling of low nanogram-level complex biological samples. As a result, ULF LC-FAIMS-MS brought unprecedented sensitivity levels and high reproducibility in bottom-up proteomic profiling. In addition, FAIMS improved the dynamic range, signal-to-noise ratios, and detection limits in ULF LC-MS-based measurements by significantly reducing chemical noise in comparison to the conventional nanoESI interface used with the same ULF LC-MS setup. Two, three, or four compensation voltages separated by at least 15 V were tested within a single LC-MS run using the FAIMS interface. The optimized ULF LC-ESI-FAIMS-MS/MS conditions resulted in identification of 2,348 ± 42 protein groups, 10,062 ± 285 peptide groups, and 15,734 ± 350 peptide-spectrum matches for 1 ng of a HeLa digest, using a 1 h gradient at the flow rate of 12 nL/min, which represents an increase by 38%, 91%, and 131% in respective identifications, as compared to the control experiment (without FAIMS). To evaluate the practical utility of the ULF LC-ESI-FAIMS-MS platform in proteomic profiling of limited samples, approximately 100, 1,000, and 10,000 U937 myeloid leukemia cells were processed, and a one-tenth of each sample was analyzed. Using the optimized conditions, we were able to reliably identify 251 ± 54, 1,135 ± 80, and 2,234 ± 25 protein groups from injected aliquots corresponding to ∼10, 100, and 1,000 processed cells.