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DOE OSTI2021

ESR1 mediated circ{sub 0}004018 suppresses angiogenesis in hepatocellular carcinoma via recruiting FUS and stabilizing TIMP2 expression

Angiogenesis has been certified to account for tumor pathobiology. Circular RNAs (circRNAs) have been demonstrated to be involved in angiogenesis-related diseases, including hepatocellular carcinoma (HCC). Nevertheless, the regulatory roles of most circRNAs remain obscure. This study aims to uncover the function of hsa{sub c}irc{sub 0}004018 on angiogenesis in HCC. Firstly, quantitative real-time RT-PCR (RT-qPCR) analyzed that circ{sub 0}004018 was definitely down-regulated in HCC. Western blot analysis was conducted to detect the protein level of fused protein in sarcoma (FUS) and TIMP metallopeptidase inhibitor 2 (TIMP2). Functional assays were carried out to assess the impacts of circ{sub 0}004018 on HCC. From the experimental results, we found that overexpression of circ{sub 0}004018 significantly inhibited angiogenesis in HCC. The regulatory mechanism of circ{sub 0}004018 in HCC was determined by chromatin immunoprecipitation (ChIP), luciferase reporter assays and RNA immunoprecipitation (RIP) assay. Therefore, we proved that estrogen receptor 1 (ESR1) mediated circ{sub 0}004018 regulated TIMP2 by recruiting FUS. A series of rescue assays verified that circ{sub 0}004018 participated in angiogenesis in HCC via modulating TIMP2. In summary, this paper disclosed that ESR1 activated circ{sub 0}004018 inhibited angiogenesis in HCC via binding to FUS and stabilizing TIMP2 expression.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

LncRNA HOTTIP from synovial fibroblast-derived exosomes: A novel molecular target for rheumatoid arthritis through the miR-1908–5p/STAT3 axis

Rheumatoid arthritis (RA) is a chronic inflammation mediated by autoimmune responses. HOTTIP, a long noncoding RNA (lncRNA), participates in cell proliferation and invasion. However, the correlation between HOTTIP and RA remains unclear. Therefore, this study aimed to clarify how HOTTIP works in RA and to investigate its role in the development of RA. Flow cytometry was used to analyze cell cycle progression. Binding between HOTTIP, signal transducer and activator of transcription 3 (STAT3) and miR-1908–5p was demonstrated by dual-luciferase assays. Quantitative real-time polymerase chain reaction (qRT–PCR) was used to measure the expression of T cell differentiation-related proteins. We found that HOTTIP was upregulated in rheumatoid arthritis synovial fibroblasts (RASFs). HOTTIP directly bound to miR-1908–5p and negatively modulated miR-1908–5p expression while positively regulating STAT3. The effects of HOTTIP overexpression on regulating the balance of the Th17/Treg cell ratio were partly reversed by miR-1908–5p overexpression. In addition, in vivo experiments demonstrated that overexpression of HOTTIP aggravated inflammation in RA mice, which was demonstrated by hematoxylin and eosin (HE) staining and the increased expression levels of CD4{sup +} interleukin (IL)-17{sup +}, forkhead Box P3 (FOXP3) and retinoid-related orphan receptor gamma-t (RORγt). In summary, our study suggests that HOTTIP plays a damaging role in RA by promoting inflammation, which may be related to the regulation of miR-1908–5p expression and the STAT3 signaling pathway. These results suggest that the regulation of HOTTIP may be a promising therapeutic strategy for RA.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

COVID-19 Biomarkers and Advanced Sensing Technologies for Point-of-Care (POC) Diagnosis

COVID-19, also known as SARS-CoV-2 is a novel, respiratory virus currently plaguing humanity. Genetically, at its core, it is a single-strand positive-sense RNA virus. It is a beta-type Coronavirus and is distinct in its structure and binding mechanism compared to other types of coronaviruses. Testing for the virus remains a challenge due to the small market available for at-home detection. Currently, there are three main types of tests for biomarker detection: viral, antigen and antibody. Reverse Transcription-Polymerase Chain Reaction (RT-PCR) remains the gold standard for viral testing. However, the lack of quantitative detection and turnaround time for results are drawbacks. This manuscript focuses on recent advances in COVID-19 detection that have lower limits of detection and faster response times than RT-PCR testing. The advancements in sensing platforms have amplified the detection levels and provided real-time results for SARS-CoV-2 spike protein detection with limits as low as 1 fg/mL in the Graphene Field Effect Transistor (FET) sensor. Additionally, using multiple biomarkers, detection levels can achieve a specificity and sensitivity level comparable to that of PCR testing. Proper biomarker selection coupled with nano sensing detection platforms are key in the widespread use of Point of Care (POC) diagnosis in COVID-19 detection.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Perimatrix of middle ear cholesteatoma: A granulation tissue with a specific transcriptomic signature

Objectives/Hypothesis: To establish comprehensive transcriptomic profiles of cholesteatoma perimatrix tissue and granulation tissue from chronic otitis media (COM) that did not develop cholesteatoma, which can indicate molecular pathways involved in the cholesteatoma perimatrix pathology and invasiveness. Study Design: Retrospective Case Series. Methods: Transcriptome data were obtained from cholesteatoma perimatrix tissue and COM granulation tissue by an Illumina iScan microarray. Differentially expressed genes (DEGs) were subsequently analyzed using both bioinformatical functional annotation and network analysis. Expression of candidate genes (MMP9 and LCN2) was validated by quantitative reverse transcription-polymerase chain reaction (qRT-PCR) on a larger group of samples. Results: Analysis of the transcriptome led to the identification of 169 differentially expressed genes between investigated tissues. Bioinformatic analysis suggested that most significant biological processes involving DEGs were previously described in cholesteatoma pathology. Network analysis identified ERBB2, TFAP2A, and TP63 as major hubs of the DEGs molecular network. Furthermore, it was observed that the cellular component most significantly enriched in DEGs was extracellular space containing 47 DEGs. Using qRT-PCR, it was confirmed that mRNA levels of the major extracellular hub (MMP9) are increased, whereas its interacting molecule (LCN2) mRNA levels were decreased in cholesteatoma perimatrix tissue compared to COM granulation tissue. Conclusions: The current study approach offers an overall look at molecular mechanisms that describe the cholesteatoma entity by focusing exclusively on the perimatrix processes in comparison to COM granulation tissue. The observed differences in gene expression between cholesteatoma perimatrix and COM granulation tissue could suggest novel markers potentially influenced by the perimatrix–matrix molecular interplay, which is not present in COM without cholesteatoma. Level of Evidence: NA. Laryngoscope, 130:E220–E227, 2020. © 2019 The American Laryngological, Rhinological and Otological Society, Inc.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

GLIDR promotes the progression of glioma by regulating the miR-4677-3p/MAGI2 axis

Gliomas are the most common and fatal primary brain tumors. Growing evidence suggests that long non-coding RNAs (lncRNAs) constitute novel and potential therapeutic targets for glioma. However, the biological role of glioblastoma down-regulated RNA (GLIDR) in glioma remains largely elusive. In the current study, we used quantitative real-time polymerase chain reaction (qRT-PCR) to detect GLIDR expression in glioma cells. Cell counting kit 8 (CCK-8) assay, colony formation assay, JC-1 staining, and flow cytometry were used to evaluate the role of GLIDR in proliferation and apoptosis of glioma cells. Western blotting was performed to assess the effect of GLIDR on the level of apoptosis-related proteins. In addition, bioinformatics prediction, RNA immunoprecipitation (RIP), RNA pull-down, and luciferase reporter gene assays were used to study the regulatory mechanisms of GLIDR in glioma. GLIDR was found to be highly expressed in glioma cells and silencing of GLIDR inhibited cell proliferation and promoted apoptosis. Functionally, GLIDR bound to miR-4677-3p that directly targeted membrane-associated guanylate kinase, WW, and PDZ domain-containing protein 2 (MAGI2). Our data showed that GLIDR affects the proliferation and apoptosis of glioma cells by targeting miR-4677-3p to regulate the expression of MAGI2. In conclusion, our study determined the oncogenic role of GLIDR in glioma, which may provide a new perspective for the treatment of glioma.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Extracellular IL-37 promotes osteogenic and odontogenic differentiation of human dental pulp stem cells via autophagy

The osteogenic and odontogenic differentiation of dental pulp stem cells (DPSCs) contribute to restoration and regeneration of dental tissue. Previous study indicated that interleukin-37 (IL-37) was an anti-inflammatory factor that affected other pro-inflammatory signals. The aim of this study was to explore the effects of IL-37 on the differentiation of DPSCs. DPSCs were cultured in growth medium with different concentrations of IL-37. We selected the optimal concentration for the following experiments by alkaline phosphatase (ALP) activity analysis, quantitative reverse-transcription polymerase chain reaction (qRT-PCR) and Western blot. Cell counting kit assay (CCK-8) and 5-Ethynyl-2-Deoxyuridine (EdU) assay were conducted to assess the effects of IL-37 on the proliferation of DPSCs. ALP activity assay and staining, alizarin red S (ARS) staining, qRT‐PCR, Western blot as well as immunofluorescence staining were conducted to assess differentiation ability of DPSCs. Western blot, immunofluorescence staining and transmission electron microscopy (TEM) were utilized to examine cell autophagy. Results showed that IL-37 enhanced the osteogenic and odontogenic differentiation ability of DPSCs with no significant influence on the proliferation of DPSCs. Autophagy in DPSCs was activated by IL-37. Activation of autophagy enhanced osteogenesis and odontogenesis of DPSCs, whereas inhibition of autophagy suppressed DPSCs osteogenic and odontogenic differentiation. In conclusion, IL-37 increased osteogenic and odontogenic differentiation via autophagy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Rapid detection of mexX in Pseudomonas aeruginosa based on CRISPR-Cas13a coupled with recombinase polymerase amplification

The principal pathogen responsible for chronic urinary tract infections, immunocompromised hosts, and cystic fibrosis patients is Pseudomonas aeruginosa , which is difficult to eradicate. Due to the extensive use of antibiotics, multidrug-resistant P. aeruginosa has evolved, complicating clinical therapy. Therefore, a rapid and efficient approach for detecting P. aeruginosa strains and their resistance genes is necessary for early clinical diagnosis and appropriate treatment. This study combines recombinase polymerase amplification (RPA) and clustered regularly interspaced short palindromic repeats-association protein 13a (CRISPR-Cas13a) to establish a one-tube and two-step reaction systems for detecting the mexX gene in P. aeruginosa . The test times for one-tube and two-step RPA-Cas13a methods were 5 and 40 min (including a 30 min RPA amplification reaction), respectively. Both methods outperform Quantitative Real-time Polymerase Chain Reactions (qRT-PCR) and traditional PCR. The limit of detection (LoD) of P. aeruginosa genome in one-tube and two-step RPA-Cas13a is 10 aM and 1 aM, respectively. Meanwhile, the designed primers have a high specificity for P. aeruginosa mexX gene. These two methods were also verified with actual samples isolated from industrial settings and demonstrated great accuracy. Furthermore, the results of the two-step RPA-Cas13a assay could also be visualized using a commercial lateral flow dipstick with a LoD of 10 fM, which is a useful adjunt to the gold-standard qRT-PCR assay in field detection. Taken together, the procedure developed in this study using RPA and CRISPR-Cas13a provides a simple and fast way for detecting resistance genes.

Zhu, Xiao-Xuan↗

DOE OSTI2020

Evaluation of Three RNA Extraction Kits with a 2019-nCoV Assay

The following characteristics of three RNA extraction kits (Norgen Biotek Total RNA Purification Kit, #17200; Bioneer AccuPrep Viral RNA Extraction Kit, #K-3033; and Promega Maxwell HT Viral TNA Kit, #AX2340) were evaluated: Limits of detection for quantitative synthetic RNA using the Centers for Disease Control and Prevention’s (CDC) 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel and the Applied Biosystems 7500 Fast Dx system; Limits of detection for positive clinical specimen using the Centers for Disease Control and Prevention’s (CDC) 2019-Novel Coronavirus (2019-nCoV) Real-Time RT-PCR Diagnostic Panel and the Applied Biosystems 7500 Fast Dx system; Ability of the lysis buffers in each kit to inactivate the virus as measured by a cell-based infectivity assay.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Emerging Trends and Technologies Used for the Identification, Detection, and Characterisation of Plant-Parasitic Nematode Infestation in Crops

Accurate identification and estimation of the population densities of microscopic, soil-dwelling plant-parasitic nematodes (PPNs) are essential, as PPNs cause significant economic losses in agricultural production systems worldwide. This study presents a comprehensive review of emerging techniques used for the identification of PPNs, including morphological identification, molecular diagnostics such as polymerase chain reaction (PCR), high-throughput sequencing, meta barcoding, remote sensing, hyperspectral analysis, and image processing. Classical morphological methods require a microscope and nematode taxonomist to identify species, which is laborious and time-consuming. Alternatively, quantitative polymerase chain reaction (qPCR) has emerged as a reliable and efficient approach for PPN identification and quantification; however, the cost associated with the reagents, instrumentation, and careful optimisation of reaction conditions can be prohibitive. High-throughput sequencing and meta-barcoding are used to study the biodiversity of all tropical groups of nematodes, not just PPNs, and are useful for describing changes in soil ecology. Convolutional neural network (CNN) methods are necessary to automate the detection and counting of PPNs from microscopic images, including complex cases like tangled nematodes. Remote sensing and hyperspectral methods offer non-invasive approaches to estimate nematode infestations and facilitate early diagnosis of plant stress caused by nematodes and rapid management of PPNs. This review provides a valuable resource for researchers, practitioners, and policymakers involved in nematology and plant protection. It highlights the importance of fast, efficient, and robust identification protocols and decision-support tools in mitigating the impact of PPNs on global agriculture and food security.

Plant Sciences↗

DOE OSTI2023

One Health Assessment of Bacillus anthracis Incidence and Detection in Anthrax-Endemic Areas of Pakistan

Anthrax, a severe zoonotic disease, is infrequently reported in anthrax-endemic regions of Pakistan. Despite clinical reports indicating its presence, particularly cutaneous anthrax, there is insufficient laboratory evidence regarding disease occurrence and environmental persistence. The present study aimed to confirm Bacillus anthracis presence, accountable for animal mortality and human infection, while exploring environmental transmission factors. Between March 2019 and July 2021, a total of 19 outbreaks were documented. Of these, 11 affected sheep/goats in Zhob district and 8 affected cattle/sheep in Bajour Agency. Clinical signs suggestive of Bacillus anthracis outbreak were observed in 11 animals. Blood and swab samples were collected for confirmation. The study followed a One Health approach, analyzing animal, environmental (soil/plant), and human samples. Of the 19 outbreaks, 11 were confirmed positive for anthrax based on growth characteristics, colony morphology, and PCR. Soil and plant root samples from the outbreak areas were collected and analyzed microscopically and molecularly. Cutaneous anthrax was observed in six humans, and swab samples were taken from the lesions. Human serum samples (n = 156) were tested for IgG antibodies against PA toxin and quantitative analysis of anthrax toxin receptor 1 (ANTXR1). Bacillus anthracis was detected in 65 out of 570 (11.40%) soil samples and 19 out of 190 (10%) plant root samples from the outbreak areas. Four out of six human samples from cutaneous anthrax lesions tested positive for Bacillus anthracis. Human anthrax seroprevalence was found to be 11% and 9% in two districts, with the highest rates among butchers and meat consumers. The highest ANTXR1 levels were observed in butchers, followed by meat consumers, farm employees, meat vendors, veterinarians, and farm owners. These findings highlight the persistence of anthrax in the region and emphasize the potential public health risks.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Effects of error, chimera, bias, and GC content on the accuracy of amplicon sequencing

ABSTRACT Targeted amplicon sequencing is widely used in microbial ecology studies. However, sequencing artifacts and amplification biases are of great concern. To identify sources of these artifacts, a systematic analysis was performed using mock communities comprised of 16S rRNA genes from 33 bacterial strains. Our results indicated that while sequencing errors were generally isolated to low-abundance operational taxonomic units, chimeric sequences were a major source of artifacts. Singleton and doubleton sequences were primarily chimeras. Formation of chimeric sequences was significantly correlated with the GC content of the targeted sequences. Low-GC-content mock community members exhibited lower rates of chimeric sequence formation. GC content also had a large impact on sequence recovery. The quantitative capacity was notably limited, with substantial recovery variations and weak correlation between anticipated and observed strain abundances. The mock community strains with higher GC content had higher recovery rates than strains with lower GC content. Amplification bias was also observed due to the differences in primer affinity. A two-step PCR strategy reduced the number of chimeric sequences by half. In addition, comparative analyses based on the mock communities showed that several widely used sequence processing pipelines/methods, including DADA2, Deblur, UCLUST, UNOISE, and UPARSE, had different advantages and disadvantages in artifact removal and rare species detection. These results are important for improving sequencing quality and reliability and developing new algorithms to process targeted amplicon sequences. IMPORTANCE Amplicon sequencing of targeted genes is the predominant approach to estimate the membership and structure of microbial communities. However, accurate reconstruction of community composition is difficult due to sequencing errors, and other methodological biases and effective approaches to overcome these challenges are essential. Using a mock community of 33 phylogenetically diverse strains, this study evaluated the effect of GC content on sequencing results and tested different approaches to improve overall sequencing accuracy while characterizing the pros and cons of popular amplicon sequence data processing approaches. The sequencing results from this study can serve as a benchmarking data set for future algorithmic improvements. Furthermore, the new insights on sequencing error, chimera formation, and GC bias from this study will help enhance the quality of amplicon sequencing studies and support the development of new data analysis approaches.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Practical Guide to Chemometric Analysis of Optical Spectroscopic Data

The methodology and mathematical treatment of several classic multivariate methods for the analysis of spectroscopic data is demonstrated in a straightforward way that can be used as a basis for teaching an undergraduate introductory course on chemometric analysis. The multivariate techniques of classical least squares (CLS), principal component regression (PCR), and partial least squares (PLS), as well as the univariate Beer’s law method have been described and compared, building students’ understanding by starting with the univariate method and progressing step by step into the multivariate methods. Equations for the production of regression vectors from training set spectral data is described and their use demonstrated for the prediction of constituent concentrations on a separate validation set of spectra. Extreme care is taken to ensure consistency in variable formatting of data matrices. This provides a key foundation to understanding how spectral data are manipulated using these different mathematical approaches for building quantitative regression models. Each method is applied to a real-world data set, and the results are discussed to show students the types of information that can be gleaned from each method. A training set comprised of 20 infrared absorbance spectra containing 3 constituents (benzene, polystyrene, and gasoline) of known composition are used to demonstrate the matrix operations for each regression method. A separate set of 12 real-world napalm samples (containing benzene, polystyrene and gasoline) are used as a validation set to demonstrate the ability to utilize the regression models on an unknown dataset. A toolbox (PNNL Chemometric Toolbox) written in MATLAB language is supplied in the Supplemental Information file and can be used as a companion for understanding the development and deployment of the chemometric algorithms described in this paper. The datasets of the infrared spectra are also supplied, allowing users to build and inspect the chemometric models on their own. Finally, the Toolbox includes scripts to assist users in loading their own datasets into MATLAB and performing CLS, PCR, and PLS on their data.

Upper-Division Undergraduate, Analytical Chemistry↗

DOE OSTI2025

Identification and mapping of quantitative trait loci for Fusarium head blight resistance in a synthetic hexaploid × hard red spring wheat population

Abstract Fusarium head blight (FHB), caused byFusarium graminearumSchwabe, is one of the most devastating diseases in wheat (Triticum aestivumL.). The synthetic hexaploid wheat line Largo was developed from a cross between the durum wheat [T. turgidumssp.durum(Desf.) Husn.] variety Langdon and theAegilops tauschiiCosson accession PI 268210, and it was previously found to have a moderate level of FHB resistance. This study was conducted to identify quantitative trait loci (QTL) associated with FHB resistance using a population of 188 recombinant inbred lines (RILs) from a cross between Largo and the susceptible wheat line ND495. The RILs were evaluated for Type II resistance in two greenhouse and two field environments. The disease severity and 90K single‐nucleotide polymorphism marker data were used for QTL analysis, which revealed six QTL on chromosomes 1D, 2D, 5B, and 7D. Four QTL (QFhb.rwg‐1D,QFhb.rwg‐5B,QFhb.rwg‐7D.1, andQFhb.rwg‐7D.3) from Largo had minor effects, whereas two QTL (QFhb.rwg‐2DandQFhb.rwg‐7D.2) from ND495 showed large effects on FHB resistance. The result suggested that ND495 may possess suppressor or susceptibility gene(s) suppressing or masking FHB resistance controlled by the resistance QTL. Among these QTL, four coincided with previously reported QTL, includingFhb9, and two (QFhb.rwg‐1DandQFhb.rwg‐7D.1) are likely novel QTL. From the six QTL regions, 10 Kompetitive allele‐specific PCR markers were developed and validated for marker‐assisted selection. The QTL detected from the resistant and susceptible parents enhance our understanding of FHB resistance expression and provide new resources for improving FHB resistance in wheat.

Genetics & Heredity↗

DOE OSTI2025

Robust collection and processing for label-free single voxel proteomics

With advanced mass spectrometry (MS)-based proteomics, genome-scale proteome coverage can be achieved from bulk tissues. However, such bulk measurement lacks spatial resolution and obscures tissue heterogeneity, precluding proteome mapping of tissue microenvironment. Here we report an integrated $\underline{w}et$ $\underline{c}ollection$ of single microscale tissue voxels and $\underline{S}urfactant$$-assisted$ $\underline{O}ne$-$\underline{P}ot$ voxel processing method termed wcSOP for robust label-free single voxel proteomics. wcSOP capitalizes on buffer droplet-assisted wet collection of a single voxel dissected by LCM into the PCR tube cap and MS-compatible surfactant-assisted one-pot voxel processing in the collection cap. This convenient method allows reproducible label-free quantification of ~900 and ~4,600 proteins for single voxels at 20 µm × 20 µm × 10 µm (close to single cells) and 200 µm × 200 µm × 10 µm (~100 cells) from fresh frozen human spleen tissue, respectively. 100s-1000s of protein signatures were spatially resolved between spleen red and white pulp regions depending on the voxel size. Region-specific signaling pathways were enriched from single voxel proteomics data. To evaluate its broad applicability, we applied wcSOP-MS to two commonly accessible, OCT-embedded and FFPE, human archived tissues. It enabled to identify spatially resolved proteome changes and enriched pathways between diseased (breast cancer tumor or AD amyloid plaque) and adjacent normal regions. Antibody-based CODEX and IHC imaging validated label-free MS quantitation for single voxel analysis. The wcSOP-MS method paves the way for routine robust single voxel proteomics and spatial proteomics.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Optimization of Molecular Methods for Detecting Duckweed-Associated Bacteria

The bacterial colonization dynamics of plants can differ between phylogenetically similar bacterial strains and in the context of complex bacterial communities. Quantitative methods that can resolve closely related bacteria within complex communities can lead to a better understanding of plant–microbe interactions. However, current methods often lack the specificity to differentiate phylogenetically similar bacterial strains. In this study, we describe molecular strategies to study duckweed–associated bacteria. We first systematically optimized a bead-beating protocol to co-isolate nucleic acids simultaneously from duckweed and bacteria. We then developed a generic fingerprinting assay to detect bacteria present in duckweed samples. To detect specific duckweed–bacterium associations, we developed a genomics-based computational pipeline to generate bacterial strain-specific primers. These strain-specific primers differentiated bacterial strains from the same genus and enabled the detection of specific duckweed–bacterium associations present in a community context. Moreover, we used these strain-specific primers to quantify the bacterial colonization of duckweed by normalization to a plant reference gene and revealed differences in colonization levels between strains from the same genus. Lastly, confocal microscopy of inoculated duckweed further supported our PCR results and showed bacterial colonization of the duckweed root–frond interface and root interior. The molecular methods introduced in this work should enable the tracking and quantification of specific plant-microbe associations within plant-microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

MOSAiC-Colorado State University Ice Spectrometer

This data set contains atmospheric ice nucleating particle (INP) measurements, using Colorado State University’s (CSU) Ice Spectrometer (IS), of filter collections taken at the U.S. DOE ARM AMF2 site onboard the R/V Polarstern P-deck during the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC) field campaign. Samples were collected from October 27, 2019 to September 24, 2020. A filter sampler was mounted approximately 15 m above ground level on a railing in proximity to (and approximately 3 m below) the Aerosol Observation System (AOS) inlet. Single-use filter units open to the atmosphere were pre-cleaned and pre-loaded with 47-mm diameter Nuclepore polycarbonate (0.2 µm pore-diameter) filters. Filters were typically drawn for a three-day period, with an average volume of air filtered of 87,000 standard liters. Total volumes were calculated through recorded daily flow rates using a mass flow meter (TSI). After collection, filters were stored and transported frozen until analysis using CSU’s IS instrument (McCluskey et al., 2018). Aerosol particles were first re-suspended in 8 mL of 0.1 µm-filtered deionized (DI) water. Aliquots of each suspension, and corresponding 11-fold dilutions, were dispensed into polymerase chain reaction (PCR) trays and placed into the aluminum blocks of the IS. Samples were cooled at approximately 0.33 °C min -1 and freezing detected optically with corresponding temperatures recorded. Cumulative INP concentrations were determined through calculating the number of INPs per mL of suspension (Vali, 1971) and converting to concentration per standard L of air by accounting for the proportion of liquid used and volume of air collected. All samples were corrected for the number of INPs on the average of four field blanks (cleaned, handled, transported, and analyzed in the same way without air flow). Two-tailed, 95% confidence intervals for binomial sampling are provided (Agresti and Coull, 1998). Select samples were also heat treated (95 °C for 20 min) to denature and deactivate biological INPs present and digested in 10% H 2 O 2 at 95 °C under UV-B for 20 min to remove any organic carbon INPs. Agresti, A, and BA Coull. 1998. "Approximate is better than “exact” for interval estimation of binomial proportions." American Statistics 52: 119–126. https://doi.org/10.2307/2685469 McCluskey, CS, J Ovadnevaite, M Rinaldi, J Atkinson, F Belosi, D Ceburnis, … and PJ DeMott. 2018. "Marine and Terrestrial Organic Ice-Nucleating Particles in Pristine Marine to Continentally Influenced Northeast Atlantic Air Masses." Journal of Geophysical Research: Atmospheres 123 (11): 6196–6212, https://doi.org/10.1029/2017JD028033 Vali, G. 1971. "Quantitative Evaluation of Experimental Results and the Heterogeneous Freezing Nucleation of Supercooled Liquids." Journal of the Atmospheric Sciences 28: 402-209. https://doi.org/10.1175/1520-0469(1971)028<0402:QEOERA>2.0.CO;2

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Carrier-assisted One-pot Sample Preparation for Targeted Proteomics Analysis of Small Numbers of Human Cells

Protein analysis of small numbers of human cells is primarily achieved by targeted proteomics with antibody-based immunoassays, which have inherent limitations (e.g., low multiplex and unavailability of antibodies for new proteins). Mass spectrometry (MS)-based targeted proteomics has emerged as an alternative because it is antibody-free, high multiplex, and has high specificity and quantitation accuracy. Recent advances in MS instrumentation make MS-based targeted proteomics possible for multiplexed quantification of highly abundant proteins in single cells. However, there is a technical challenge for effective processing of single cells with minimal sample loss for MS analysis. To address this issue, we have recently developed a convenient protein carrier-assisted one-pot sample preparation coupled with liquid chromatography (LC) - selected reaction monitoring (SRM) termed cLC-SRM for targeted proteomics analysis of small numbers of human cells. This method capitalizes on using the combined excessive exogenous protein as a carrier and low-volume one-pot processing to greatly reduce surface adsorption losses as well as high-specificity LC-SRM to effectively address the increased dynamic concentration range due to the addition of exogeneous carrier protein. Its utility has been demonstrated by accurate quantification of most moderately abundant proteins in small numbers of cells (e.g., 10-100 cells) and highly abundant proteins in single cells. The easy-to-implement features and no need for specific devices make this method readily accessible to most proteomics laboratories. In this study, we have provided a detailed protocol for cLC-SRM analysis of small numbers of human cells including cell sorting, cell lysis and digestion, LC-SRM analysis, and data analysis. Further improvements in detection sensitivity and sample throughput are needed towards targeted single-cell proteomics analysis. We anticipate that cLC-SRM will be broadly applied to biomedical research and systems biology with the potential of facilitating precision medicine.

60 APPLIED LIFE SCIENCES↗