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ABSTRACT BACKGROUND Lower respiratory tract infection (LRTI) including pneumonia, bronchitis, and bronchiolitis is the sixth leading cause of mortality around the world and leading cause of

death in children under 5 years. Systemic immune response to viral infection is well characterized. However, there is little data regarding the immune response at the upper respiratory tract

mucosa. The upper respiratory mucosa is the site of viral entry, initial replication and the first barrier against respiratory infections. Lower respiratory tract samples can be challenging

to obtain and require more invasive procedures. However, nasal wash (NW) samples from the upper respiratory tract can be obtained with minimal discomfort to the patient. METHOD In a pilot

study, we developed a protocol using NW samples obtained from hospitalized children with LRTI that enables single cell RNA sequencing (scRNA-seq) after the NW sample is methanol-fixed.

RESULTS We found no significant changes in scRNA-seq qualitative and quantitative parameters between methanol-fixed and fresh NW samples. CONCLUSIONS We present a novel protocol to enable

scRNA-seq in NW samples from children admitted with LRTI. With the inherent challenges associated with clinical samples, the protocol described allows for processing flexibility as well as

multicenter collaboration. IMPACT * There are no significant differences in scRNA-seq qualitative and quantitative parameters between methanol fixed and fresh Pediatric Nasal wash samples. *

The study demonstrates the effectiveness of methanol fixation process on preserving respiratory samples for single cell sequencing. * This enables Pediatric Nasal wash specimen for single

cell RNA sequencing in pediatric patients with respiratory tract infection and allows processing flexibility and multicenter collaboration. You have full access to this article via your

institution. Download PDF SIMILAR CONTENT BEING VIEWED BY OTHERS A FAST, LOW-COST, ROBUST AND HIGH-THROUGHPUT METHOD FOR VIRAL NUCLEIC ACID ISOLATION BASED ON NAXTRA MAGNETIC NANOPARTICLES

Article Open access 20 July 2023 HOST DNA DEPLETION ON FROZEN HUMAN RESPIRATORY SAMPLES ENABLES SUCCESSFUL METAGENOMIC SEQUENCING FOR MICROBIOME STUDIES Article Open access 28 November 2024

SPATIALLY RESOLVED SINGLE-CELL ATLAS UNVEILS A DISTINCT CELLULAR SIGNATURE OF FATAL LUNG COVID-19 IN A MALAWIAN POPULATION Article Open access 20 November 2024 INTRODUCTION Lower respiratory

tract infection (LRTI) including pneumonia, bronchitis, and bronchiolitis is the sixth leading cause of mortality around the world and the most common cause of death in children under 5

years old.1 Respiratory syncytial virus (RSV) is the leading cause of LRTI worldwide with 33.1 million LRTI episodes, 3.2 million hospitalizations, and 118,000 deaths in 2015.2 The symptoms

can vary from mild or asymptomatic to severe symptoms with respiratory distress that may lead to respiratory failure and subsequent need for mechanical ventilation.3 Natural infection is not

protective against reinfection4 and at this moment there is no available vaccine for RSV but multiple candidates are in clinical trials stage.5 Systemic immune response to respiratory

viruses is characterized by activation of innate immunity as a first line of defense and subsequent adaptive immunity activation, both contributing to the immunopathogenesis of respiratory

viral disease. However, there is little data regarding the immune response at the upper respiratory tract mucosa as part of the innate immunity and its role in regulating immune response.6

The upper respiratory mucosa is the site of entry and initial replication as well as the first barrier against respiratory infections.7 Lower respiratory samples can be challenging to obtain

and require more invasive procedures. However, nasal wash samples from the upper respiratory tract can be obtained with minimal discomfort to the patient,8 furthermore, upper airway suction

is standard of care during a viral respiratory infection.9 Evaluating the upper respiratory mucosal immunology can increase our understanding of the lower respiratory tract response to

respiratory infection. In addition, a better knowledge of the mucosal immune response during viral infection could aid the development of new therapeutics as well as mucosal

vaccines.10,11There is limited characterization of the upper respiratory tract mucosal immunity at a genomic level during viral infection. Single-cell RNA sequencing (scRNA-seq) could be a

powerful tool to evaluate the mucosal cell biology. Single cell RNA sequencing can generate a comprehensive transcriptional map of human cells12 allowing for a better characterization of

cell recruitment and transcriptional activity in the upper airway during a viral respiratory infection.13 However, one of the limitation of scRNA-seq is the need of high quality fresh and

viable samples to have a successful sequencing.14 The vast majority of scRNA-seq are performed with recently obtained and processed samples. Clinical samples pose a challenge for scRNA-seq

due to unpredictability of patient enrollment and sample collection. In addition, clinical samples can have low number of cells, poor viability, time from collection to

processing-to-sequencing can vary affecting the performance of such samples.15 Methanol fixation protocol designed for scRNA-seq can help with these challenges. Published data using methanol

fixation on peripheral blood mononuclear cells (PBMCs)16 describe good quality and quantity for subsequent scRNA-seq. To this end, we developed a protocol using nasal wash (NW) samples

obtained from pediatric patients hospitalized with LRTI. We describe a protocol that enables scRNA-seq using fresh and methanol-fixed NW samples. METHODS SUBJECT POPULATION We enrolled

hospitalized children less than or equal to 24 months with the diagnosis of lower respiratory tract infection (LRTI). Age, biological sex and ethnicity were collected via electronica medical

records (EMR) review. Parental consent was obtained for each subject. The Sanford Health Institutional Review Board approved the study. SAMPLE COLLECTION Nasal wash (NW) samples were

collected within 48 h of hospitalization. Nasal wash samples were obtained by gently instilling 3 cc of normal saline in each naris with subsequent suctioning into a nasal trap (Mucus

Specimen Trap Busse, Thermo Fischer Scientific, MA). The sample was placed in wet ice and transported to the laboratory for further processing (Fig. 1). NASAL WASH SAMPLE PROCESSING Two to

four hours after sample collection, the sample was processed with the goal of obtaining a cell suspension without mucus or any other debris for further scRNA-seq. First, the sample was

transferred to a conical Falcon tube (Fischer Scientific, Hampton, NH) that contained 25 ml of Roswell Park Memorial Institute (RPMI) 1640 media (Fisher Scientific) plus 10% Fetal Bovine

Serum (FBS, Fisher Scientific). The sample was pipetted slowly and gently up-and-down to break down the mucus with a 25 to 50 ml serological pipette, for approximately 2–5 s (_breakdown

mucus step_, Fig. 1). Then the sample was centrifuged at 235 G-force (xg) for 10 min, 4 °C. After discarding the supernatant carefully and avoiding any significant pellet suctioning (_spin

& discard step_) we added RPMI media + 10% FBS to top of the tube and repeated the breakdown mucus and spin & discard steps until there was no visible mucus left in the sample. Once

the sample had no visible mucus, we resuspended the sample in 10 ml of RPMI + 10% FBS and put through a 70 μm cell strainer (Falcon Cell Strainers Nylon Mesh, Fischer Scientific) to get rid

of any debris. We then spun the sample for five minutes at 235 g, 4 °C and resuspended the sample in one-ml RPMI + 10%FBS for cell counting by an automated hemocytometer. After cell count,

the sample was processed for either: a) fresh sample single cell RNA sequencing or b) Methanol fixation, rehydration and subsequent single cell RNA sequencing. PROCESSING FOR SINGLE CELL RNA

SEQUENCING FOR FRESH SAMPLE After the removal of debris and mucus as noted above, a volume of 15–20 μl of the specimen with concentration ranging from 700–1200 cells/μl went directly for

further library preparation. FOR METHANOL FIXATION After the removal of debris and mucus as noted above, we centrifuged the cells at 300 × _g_ for five minutes at 4 °C. Then we discarded the

supernatant without disrupting the cell pellet. Using a wide-bore pipette tip, we added one ml of cold 1X DPBS (HyClone Dulbecco’s Phosphate Buffered Saline: Liquid, Cytiva, Fischer

Scientific); concentration of 1 ml for 1–2 million cells and gently mixed until cells are resuspended. Centrifuged the cell suspension again at 300 × _g_ for 5 min at 4 °C. We repeated this

step twice in order to remove any RPMI and FBS. After removing the supernatant, we resuspended the pellet with 200 μl of cold DPBS per one million cells. Then, we added 800 µl of cold

(stored at −20 °C) 100% methanol per one million cells (≥99.9% Methanol, Fischer scientific). The methanol was added in a drop-by-drop fashion while gently stirring the cell suspension with

the pipette tip in the 15 ml conical tube to avoid cell clumping. We incubated the cells for 30 min at −20 °C. At this point fixed cells can be stored at −20 °C or −80 °C for up to 6 weeks.

REHYDRATION: POST-METHANOL FIXATION First, we needed to put the methanol-fixed cells on ice for five minutes to reach the wet ice temperature, 4 °C. Secondly, we centrifuged the fixed cells

at 1000 × _g_ for 5 min at 4 °C. After removing the supernatant without disrupting the cell pellet, we added the rehydration buffer (Supplementary Table 1) to obtain a concentration ranging

from 700–1200 cells/µl with consideration that 50% of cells were lost during the fixation. After rehydration, cells underwent single cell RNA sequencing. LIBRARY PREPARATION For each sample,

cells were resuspended in a volume to yield cell concentration of 700–1200 cells/µl. According to manufacturer’s instructions,17 8500 cells were loaded into Chromium Next GEM Chip G in

reaction mix containing reverse transcription reagents for GEM (Gel beads-in-emulsion) generation. Following GEM generation, full-length cDNAs were produced from poly-adenylated mRNA by

reverse transcription. After this, cDNAs were cleaned up and the cDNA amplified using 12 amplification cycles. The amplified cDNA is cleaned up with SPRIselect (Beckman Coulter, Brea,

California) and 1 µl of the cDNA is run on a bioanalyzer using High sensitivity DNA kit (Agilent, Santa Clara, California) to check the quality and concentration. A portion of the cDNA was

used for library preparation in subsequent steps of fragmentation, end repair, A-tailing and adapter ligation. After cleanup following these steps, samples were amplified with dual sample

indexes (to enable multiplexing during sequencing) to yield Illumina-compatible single cell cDNA libraries. PARAMETERS USED TO EVALUATE SAMPLE QUALITY In order to determine the appropriate

quality of fixed versus fresh NW sample, we utilized three primary established parameters for successful single cell sequencing.18 The parameters and tools to evaluate quality were: (a)

FASTQC—this allows to calculate the overall quality of the sequencing run, considered as the first quality checkpoint,19,20 (b) Mitochondrial reads/transcripts—which are known to be an

indicator of cell damage and degradation, and mitochondrial reads of 10% or more was used a cutoff point to mark cells dead or dying (Fig. 3)21 and (c) Number of total reads per cell: the

recommended sequencing depth between 30,000 and 70,000 total reads per cell for 10X Genomics projects to classify cell types.22 Lastly, we evaluated if the methanol fixation protocol could

affect cell clustering and cell type identification by applying ‘FindAllMarkers’ in Seurat’s function to identify the marker for each of the clusters in the uniform manifold approximation

and projection (UMAP) representation,23 and applying a Kolmogorov–Smirnov test as non-parametric test on paired samples to compare the changes of distance between the clusters after

fixation.24 The quality control parameters we used were calculated by using the R software package Seurat (v4.0). RESULTS NASAL WASH SAMPLES: FRESH PROTOCOL VS METHANOL FIXATION PROTOCOL

First, we decided to perform a qualitative and quantitative comparison of the two methods applied on the same 3 subjects, one nasal wash from each subject processed by both methods: Fresh

samples with 11,917 sequenced cells vs. Methanol-fixed samples with 14,197 sequenced cells (Table 1). FASTQC yielded that fresh NW samples reads had a high average quality score with no

increases at the lower quality values and the fixed methanol samples were able to keep the high average quality score after fixation and rehydration (Fig. 2). In regards of mitochondrial

reads as an indicator for low quality cells,21 we eliminated dead or dying cells that had more than 10% mitochondrial reads (Fig. 3). As expected, we found that the mitochondrial transcripts

percentage was decreased after methanol fixation (median = 0.21) compared to fresh samples (median = 0.62) (Table 1 and Fig. 3). Immediate methanol fixation of the samples was able to

protect the cell integrity from the downstream processing steps that happen during GEM (Gel beads-in-emulsion) generation. Fresh samples are more fragile as observed previously.16 Then we

assessed the size of the cDNA library as a surrogate of quality suitable for sequencing.25 We found no difference in cDNA size between fresh NW and methanol-fixed samples. The next step was

to compare the total reads per cell in samples between methods. We found no statistical difference in total reads per cell after methanol fixation (_p_ = 0.22) using Mann–Whitney test. Then,

using the scRNA-seq transcriptomic data (all transcripts), we evaluated cell clustering to assess if methanol fixation can affect cell clustering and dispersion. We found no significant

difference between paired fresh and methanol-fixed samples [_p_ = 0.84, 0.19 and 0.9 (Fig. 4)], indicating that methanol fixation does not alter scRNA-seq transcriptomic data. Using Garnett,

a tool for rapidly annotating cell types in single-cell transcriptional profiling datasets,26 we determined the occurrence of different immune cell types in the paired samples. The

frequency of the identified cell types in fresh and methanol-fixed samples was very similar, statistically indifferent (Fig. 5). Lastly, we compared the two methods applied on different

subjects, fresh NW samples from 30 subjects (92,650 sequenced cells) and methanol-fixed samples from 11 subjects (57,969 sequenced cells). We found no statistical differences in cell

viability and number of cells per sample (Table 2). Cell viability and cell number for the individual samples are shown in Supplementary Table 3. The median mitochondrial reads percentage in

fixed NW samples was lower compared to the median of mitochondrial reads percentage in fresh NW samples (0.26 versus 0.67 respectively; Table 2), indicating again that methanol fixation of

the samples preserved cell integrity during sample processing for scRNA-seq. Total reads per cell in fresh NW (_n_ = 30) and fixed NW (_n_ = 11) samples were also compared. There was a

higher number of reads per cell in fresh NW samples (Table 2). Despite these differences, we had sufficient reads in fixed NW samples to classify cell types and detect gene expression for

scRNA-seq.22 DISCUSSION To our knowledge, this is the first study describing a successful protocol for processing NW samples from pediatric patients and applying methanol fixation to

preserve samples for further scRNA-seq. Methanol fixation is an effective way to preserve cell nucleic acid with significant reversion of the denatured nucleic acid to its original state

after rehydration.27 Our methanol-fixed NW cells from nasal wash samples were preserved for more than 2 weeks (median = 10 days, IQR = 5.5–13) and were able to yield sufficient quantity and

quality for scRNA-seq measured by multiple quantitative and qualitative parameters. We found high quality score using FASTQC. Complementary DNA library produced from methanol-fixed cells

were undistinguishable compared with fresh NW samples. Consistent with published literature,16 mitochondrial reads after fixation decreased when compared with fresh NW samples, which means

that fixation by methanol was able to preserve the integrity of cells without adding stress during preservation. Despite having differences in number of total reads compared with fresh

samples, the quality or quantity of RNA from fixed samples was sufficient for further scRNA-seq analysis. Transcriptomic analysis revealed unaltered cell clustering after fixation, which

means the cell identification and transcriptomic profile can be successfully preserved (Figs. 4 and 5).16,28,29 Methanol fixation has several advantage compared to other applicable

preservation methods like cryopreservation30 which is compatible with scRNA-seq as a technique to minimize the batch effect.31 Cryopreservation and thawing method is putting high stress on

cells because of the toxicity of DMSO freezing medium,32 which leads to significant increase in mitochondrial reads in some cells like epithelial cells33 and associated with significant

changes in gene expression.34 In contrast, in our study, methanol fixation showed no significant cellular stress that could lead to significantly lower cell quality, which, in turn, can

hinder the sequencing. In addition, the transcriptomic profile of the cells is preserved based on our results and published work.16,29 Additionally, sample transportation after methanol

fixation is simpler and does not require liquid nitrogen compared with the cryopreservation method. There are limitations to our study. While we were able to keep track of sample

preservation time in −80 °C (Supplementary Table 2), we did not keep records between sample acquisition and processing time. Our estimate is that the time intervals between sample collection

and the initial processing were 2 to 4 h. Delays in processing time can affect cell viability hindering the downstream protocol. All our subjects were hospitalized with LRTI, hence there is

significant inflammation in the upper airway due to the infection. However, we do not have any information for subjects with potential fewer number of cells in the upper airways due to

infection such as outpatient subjects seen for LRTI without requiring hospitalization. Methanol fixation enhances the scope of single cell RNA sequencing, especially in rare tumors, while

the specimens are available with either lack of the equipment or the availability allowing to identify more rare cell subpopulations. Preserving the tissue/cell samples for later single cell

sequencing is extending the outreach arms of the research facility to approach overseas areas to improve developmental research and expand human cell atlases. In conclusion, we present a

novel protocol to enable scRNA-seq in nasal wash samples from pediatric patients admitted with viral LRTI. Considering the challenges of clinical samples, the protocol described allows for

processing flexibility as well as multicenter collaboration. DATA AVAILABILITY All data generated or analyzed during this study are included in this published article and its supplementary

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PubMed  Google Scholar  Download references ACKNOWLEDGEMENTS This project is supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of

the National Institutes of Health under grant number 5P20GM12134. AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Environmental Influences on Health and Disease Group, Sanford Research, Sioux

Falls, SD, USA Khaled A. Ismail & Santiago M. C. Lopez * Functional Genomics and Bioinformatics Core, Sioux Falls, SD, USA Malini Mukherjee & Michael S. Kareta * Genetics &

Genomics Group, Sanford Research, Sioux Falls, SD, USA Michael S. Kareta * Department of Pediatrics, Sanford School of Medicine-University of South Dakota, Sioux Falls, SD, USA Michael S.

Kareta & Santiago M. C. Lopez * Children’s Health Specialty Clinic, Sanford Children’s Hospital, Sioux Falls, SD, USA Santiago M. C. Lopez Authors * Khaled A. Ismail View author

publications You can also search for this author inPubMed Google Scholar * Malini Mukherjee View author publications You can also search for this author inPubMed Google Scholar * Michael S.

Kareta View author publications You can also search for this author inPubMed Google Scholar * Santiago M. C. Lopez View author publications You can also search for this author inPubMed 

Google Scholar CONTRIBUTIONS Each author has met the Pediatric Research authorship requirements. S.M.C.L. and K.A.I. completed the conception and design. K.A.I. and M.M. carried out the

experiment. M.S.K., S.M.C.L. and K.A.I. completed acquisition of data, analysis and interpretation of data. S.M.C.L., K.A.I., M.M. and M.S.K. completed drafting the article and revising it

critically for important intellectual content. S.M.C.L. completed the final approval of the version to be published. CORRESPONDING AUTHOR Correspondence to Santiago M. C. Lopez. ETHICS

DECLARATIONS COMPETING INTERESTS The authors declare no competing interests. CONSENT TO PARTICIPATE Patient’s parental consent was required for the paper. ADDITIONAL INFORMATION PUBLISHER’S

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permissions ABOUT THIS ARTICLE CITE THIS ARTICLE Ismail, K.A., Mukherjee, M., Kareta, M.S. _et al._ Enabling methanol fixation of pediatric nasal wash during respiratory illness for single

cell sequencing in comparison with fresh samples. _Pediatr Res_ 95, 835–842 (2024). https://doi.org/10.1038/s41390-023-02780-2 Download citation * Received: 23 March 2023 * Revised: 21 June

2023 * Accepted: 24 July 2023 * Published: 28 September 2023 * Issue Date: February 2024 * DOI: https://doi.org/10.1038/s41390-023-02780-2 SHARE THIS ARTICLE Anyone you share the following

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