DOI: 10.5281/zenodo.11100300
title: Longitudinal single-cell RNA sequencing of 55,260 capillary PBMCs from 2 donors with ME/CFS before, during, and after antibiotic treatment

description: Sample Procurement

Samples were self-collected directly from participants as part of RemissionBiome's pilot study, and processed by ImYoo. For additional details on the experiment, see ImYoo's blog post and corresponding comments.

Sample Processing

Whole capillary blood samples were self-collected from participants using the TAP II device. Samples were kept in a temperature stable thermos or styrofoam cooler with ice packs and shipped with overnight shipping to ImYoo labs. Cells were isolated using EasySep Direct Human PBMC Isolation Kit (STEMCELL Technologies Catalog #19654) and cryopreserved using CryoStor CS10 (STEMCELL Technologies Catalog #07930). Upon thawing, samples were labeled in accordance with the MULTI-seq protocol (https://www.nature.com/articles/s41592-019-0433-8) and then processed on a 10X Genomics Chromium, using the Chromium Next GEM Single Cell 3’ HT Kit v3.1 (10X Genomics Product Code 1000370). DNA libraries were sequenced on a Complete Genomics DNBSEQ-G400 sequencer.

Data Processing

Transcriptomic sequencing data was processed using Cell Ranger v7.0.1 with default parameters. Multiplexing oligo sequencing data was processed through a custom python script that counts the number of occurrences of each sample barcode sequence and assigns it to the corresponding cell barcode. Samples were demultiplexed using a custom algorithm that estimates the background sample barcode counts, and assigns each cell a probability of belonging to each sample. Cell typing was done by training an scVI model on all cells with default parameters, and "library" as the batch_key. The latent space was then used to perform leiden clustering, and clusters were mapped to cell types based on common marker gene expression.

Differential Expression

Differential expression was calculated using DEseq2. For each cluster and cell type, cells from the same sample in the same participant were summed together to create a pseudocell, and passed as pseudobulked samples into DESeq2 to compare "Event" samples to "Baseline" samples.

Metadata Fields



barcode: 10X cell barcode

sample_id: Unique ID for the experimental sample that was processed with 10x Chromium, could have come from the same biological sample (identified by source_sample_id)

condition: Whether this sample is before ("Baseline"), during ("Event"), or after ("New Baseline") the antibiotic intervention

participant_id: Unique ID for participant. There are two participants: P363, and P364. P363 experienced a full remission event, while P364 did not.

extracted_on: The date and time the blood was extracted

cell_barcoding_run_id: Unique ID for the 10x Chromium cell barcoding run in which that sample was processed. Multiple samples can be processed in a cell barcoding run.

extraction_type: Whether the PBMCs were isolated from Venous or Capillary blood

lane: ID of which Chromium chip lane the cell came from

sample_processing_delay_seconds: The amount of time (in seconds) between when the blood was extracted from the participant and when PBMC isolation + cryopreservation was performed

cell_barcoding_delay_days: How long PBMC samples were stored in liquid nitrogen prior to being thawed and processed on 10x

cell_barcoding_protocol: Which single cell RNA sequencing experimental protocol was used. Here all samples were processed with 10x v3.1 chemistry.

library: Concatenation of columns Cell Barcoding Runs and Lane to provide a unique ID for experimental processing batch (i.e. the DNA library)

leiden: The cluster this cell belongs to after automatic cell clustering

cell_type: Manually labeled cell type

source_sample_id: Some samples may be derived from the same originating whole blood sample. This field specifies the source of the whole blood sample.