Together, these data and resources provide a platform to leverage the regenerative abilities of neonatal skin to develop clinically tractable solutions that promote the regeneration of adult tissue.Scars are a serious health concern for burn victims and individuals with skin conditions associated with wound healing. Here, we identify regenerative factors in neonatal murine skin that transforms adult skin to regenerate instead of only repairing wounds with a scar, without perturbing development and homeostasis. Using scRNA-seq to probe unsorted cells from regenerating, scarring, homeostatic, and developing skin, we identified neonatal papillary fibroblasts that form a transient regenerative cell type that promotes healthy skin regeneration in young skin. These fibroblasts are defined by the expression of a canonical Wnt transcription factor Lef1 and using gain- and loss of function genetic mouse models, we demonstrate that Lef1 expression in fibroblasts primes the adult skin macroenvironment to enhance skin repair, including regeneration of hair follicles with arrector pili muscles in healed wounds. Finally, we share our genomic data in an interactive, searchable companion website ( Understanding how to induce skin regeneration instead of scarring will have broad implications clinically and cosmetically . One of Human and mouse skin are similar in their overall structural complexity, indicating that mouse skin can be a useful model to study skin development and wound repair . Murine Gpx3, Plac8, and Mest, which recently has been shown to contribute to scar formation .We subset the fibroblast clusters 3, 4, 16 and re-clustered them by performing an integration analysis . This alCochlin (Coch), an inner ear ECM protein, contained 80.8% of cells from the homeostasis condition and a DP/DS sub-clusters (cluster 6) contained 95.0% of cells from the homeostasis condition. The papillary fibroblast cluster (cluster 0) contained 98.1% of cells from the developing skin condition. The DP sub-cluster (cluster 7) consisted of 56.5% cells from the developing condition and 37.1% cells from the regenerating condition. These results indicate that there is a distinct separation based on condition between fibroblast sub-types neonatal papillary fibroblasts versus reticular/hypodermal/fascia. Moreover, regenerating, and scarring conditions were present in similar proportions across multiple fibroblasts subtypes, besides clusters of hypodermal and fascia cells that were mainly composed of the scarring condition. This suggested that both wounding conditions shared similar cellular and molecular signatures that may be driven by the wound healing process.To identify conditions that are represented within specific fibroblast subtypes, we quantified the percentage of cells from each condition within the sub-clusters . Our resSince our goal was to identify a cell type that uniquely represented the ability to support hair follicle formation that does not include a wound induced signature, we focused on cluster 0 which are developing fibroblasts. Developing fibroblasts migrate into wounds and support the reformation of hair follicles . In homePdgfra and Twist2 (Dpp4+/Dlk1-/Ly6a-), reticular (Dpp4-/Dlk1+/Ly6a+/-) and hypodermal fibroblasts (Dpp4-/Dlk1-/Ly6a+) on the developing scRNA-seq UMAP  in wounds 1 cmr larger . To testat 24dpw . Our anaat 24dpw . There wat 24dpw . The nonat 24dpw  and wereLef1 expression in the dermis induces skin to support hair follicle regeneration in wounds with variation depends on the timepoints and hair follicle cycle.Wound healing studies utilize a standardized approach to account for the hair follicle cycle, which influences the wound healing process . ConsequNoggin, Tgfb, and fibroblast markers such as Pdgfra. Inhibitors include the BMP signaling pathway. These activators and inhibitors have been previously shown to modulate Lef1 activity  (Cat# 008712). The ROSA26-CAG-flox-GFP-STOP-flox-Lef1 and Lef1-flox-Exon7,8-flox mice (RRID:MGI:5447957) were a kind gift and have been previously described  squares were excised using surgical scissors. Wounds were harvested at 7 dpw, 14 dpw, 24 dpw, and 30 dpw.All wounding experiments were done in accordance with the guidelines from approved protocols Washington State University IACUC. Mice were wounded at post-natal day (P) 2, P24, P40 and P90 as stated in the results section. All wounding experiments were carried out with mice under anesthetization. The dorsal hair was shaved, and wounding areas were disinfected. For full-thickness circular wound, 2 mm and 8 mm punch biopsy and surgical scissors were used to create circular wounds on P2 and P24/P40 mice, respectively. For large wounds, 1.44 cmThis procedure was described in SCR_017344)(Cellranger version 3.0.2). FASTQ files for this manuscript can be access at NCBI Geo-Datasets: GSE153596. The outputs of CellRanger alignment were used to create loom files by Velocyto ‘run10x’ function (SCR_018168) to perform RNA Velocity analysis   . Data wehttps://github.com/DriskellLab/Priming-Skin-to-Regenerate-by-Inducing-Lef1-Expression-in-Fibroblasts-; copy archived at https://github.com/elifesciences-publications/Priming-Skin-to-Regenerate-by-Inducing-Lef1-Expression-in-Fibroblasts-; Neighborhood graph of cells was computed using PCA presentation . The graph was embedded in two dimensions using Uniform Manifold Approximation and Projection (UMAP) as suggested by Scanpy developers. Clusters of cell types were defined by Louvain and Leiden method for community detection on the generated UMAP graph at resolution of 0.2. The analysis pipeline is published on the Driskell lab Github page as Jupyter Notebook (The microarray data were previously published (GEO GSE11186) . RMA nor In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:eLife.Overall this is an interesting paper whose ssRNA seq dataset and experimental analysis of phenotypes provides a valuable resource for investigating gene expression differences associated with key phases of skin development and repair. The enhancement of HF regeneration upon Lef1 overexpression is a striking result and will be of general interest to many fields including developmental, stem cell, and epithelial biologists. The work is well conducted, the results are new, and significant for skin wound healing and HF regeneration, and in sum a good fit for Decision letter after peer review:eLife. Your article has been reviewed by three peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Kathryn Cheah as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "Lef1 expression in fibroblasts maintains developmental potential in adult skin to regenerate wounds" for consideration by The reviewers have discussed the reviews with one another and the Reviewing Editor has drafted this decision to help you prepare a revised submission.eLife". Please let us know if you would like to pursue this option. As the editors have judged that your manuscript is of interest, but as described below that additional experiments are required before it is published, we would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). First, because many researchers have temporarily lost access to the labs, we will give authors as much time as they need to submit revised manuscripts. We are also offering, if you choose, to post the manuscript to bioRxiv  along with this decision letter and a formal designation that the manuscript is "in revision at Summary:eLife.Overall this is an interesting paper whose ssRNA seq dataset and experimental analysis of phenotypes provides a valuable resource for investigating gene expression differences associated with key phases of skin development and repair. The enhancement of HF regeneration upon Lef1 overexpression is a striking result and will be of general interest to many fields including developmental, stem cell, and epithelial biologists. The work is well conducted, the results are new, and significant for skin wound healing and HF regeneration, and in sum a good fit for Essential revisions:The overall tone of all reviewers is enthusiastic and favorable, however with very important points raised:1) Dermo1-Cre seems not specific to fibroblasts (and it is non-inducible). Ideally this should be addressed by using an inducible/more specific Cre mouse line. However, as the enhancement of HF regeneration is an exciting finding by itself and a new mouse model is likely out of scope of a revision, this point could be addressed textually by changing the conclusions to reference stromal cells instead of fibroblasts specifically.2) The interpretation of the scRNA data should be bolstered with additional analyses. It is important for the authors to revisit the data and figures , and carefully state the actual results and conclusions supporting their claims and following next steps in the manuscript.a) ScRNA-seq analysis was superficial in relation to regeneration versus repair, especially comparison of the time points that model regeneration and scarring. Does velocity analysis predicting Lef1, or other genes, driving differentiation of one population of fibroblasts into a papillary fibroblast or DP-like state? Do multiple fibroblast subsets follow this trajectory? How do these finding compare between the two wounding time points? Does gene ontology suggest differences within one subcluster of fibroblasts between two conditions or are the major differences in the gene expression profile/function associated with each subcluster? A more complete analysis of this could shed more light on the involvement of fibroblast lineages in regenerative versus reparative healing.b) From the ssRNA seq analysis the authors state "we identify Developing papillary fibroblasts as a transient cell population that is defined by Lef1 expression.", but this is not clear from the ssRNA seq analysis. In Figure 2—figure supplement 1, Lef1 expression seems to be largely excluded from cells within the Dpp4 expression cluster (cluster 2), and Dkk1 (Cluster 0), which define the major papillary FB clusters. Can the authors expand upon how the Velocity Analysis identifies different genes than overlaying relative expression levels on the UMAPS?3) Surrounding the claim of a transient papillary fibroblast population (which is an important part in their paper), several parts are unclear;I.e. they could/should explore the fibroblast populations of all conditions to compare regeneration vs. scaring and regeneration vs. development .which of the two papillary fibroblast population(s) is/are transient? How to explain the rather minor overlap of Lef1 expression with these two papillary fib populations? Where are the two populations in situ in developing and in regenerating skin?4) Given that the WIHN generates a significant amount of cysts, the authors have to down-tone their statement of "without adverse phenotype". As the authors also refer to Hedgehog-pathway induced de novo HF formation (a model giving rise to tumors and new HFs), they likely meant that their model does not induce apparent tumors (the cysts look different compared to the obvious BCC-like lesions trough Hh-pathway activation) – however the authors totally neglect the fact (don't mention) that the mice apparently develop cysts in addition to HFs in wounds.Figure 5E, G, J. The regenerated HFs appear very abnormal and cyst-like. The authors state several times in the paper that Lef1 overexpression enhances regeneration without other adverse phenotypes, but these regenerated structure are very abnormal. Are they cancerous? P90 wounds appear to generate a significant amount of cysts; is this representative for all conditions or something more specific for the P90 timepoint? Essential revisions:The overall tone of all reviewers is enthusiastic and favorable, however with very important points raised:1) Dermo1-Cre seems not specific to fibroblasts (and it is non-inducible). Ideally this should be addressed by using an inducible/more specific Cre mouse line. However, as the enhancement of HF regeneration is an exciting finding by itself and a new mouse model is likely out of scope of a revision, this point could be addressed textually by changing the conclusions to reference stromal cells instead of fibroblasts specifically.We thank the reviewers for this comment and have addressed the concerns by changing the text as suggested.2) The interpretation of the scRNA data should be bolstered with additional analyses. It is important for the authors to revisit the data and figures , and carefully state the actual results and conclusions supporting their claims and following next steps in the manuscript.The below points by the reviewers have been helpful in revising our manuscript and we have addressed the points as stated below. In short, we have rewritten portions of the text in the manuscript that refers to Figure 1 and Figure 2.a) ScRNA-seq analysis was superficial in relation to regeneration versus repair, especially comparison of the time points that model regeneration and scarring. Does velocity analysis predicting Lef1, or other genes, driving differentiation of one population of fibroblasts into a papillary fibroblast or DP-like state? Do multiple fibroblast subsets follow this trajectory? How do these finding compare between the two wounding time points? Does gene ontology suggest differences within one subcluster of fibroblasts between two conditions or are the major differences in the gene expression profile/function associated with each subcluster? A more complete analysis of this could shed more light on the involvement of fibroblast lineages in regenerative versus reparative healing.The reviewers have suggested an analysis that we have now performed and present as new Figure 2—figure supplement 2. This comparison is represented by an integrated clustering analysis mapped by marker genes and a velocity analysis. We utilized a combination of markers to create a cell atlas of each UMAP. This included Corin, Acan, Acta2, Crabp1, Mest, and Plac8.Importantly, our velocity analysis does not predict Lef1 to drive differentiation of fibroblasts to papillary or DP like state, shown in our new Figure 2—figure supplement 2A-C. Overall dermal papilla from regenerating wounds appeared to be separated from the main population with a trajectory that might be connected to the main population. The upper fibroblast population from regenerating wounds clusters closely with the upper fibroblast population of scarring wounds, but does not show an overall integrating velocity .In this manuscript we have focused on exploring the Developing skin condition for regenerative molecular signals. However, we performed a differential expression on all cells within regenerating and scarring conditions, which revealed differences gene ontology and key genes between points. Particularly the expression of Gpx3, a fascia marker being upregulated in scarring wounds. This is now a new Figure 2—figure supplement 2.b) From the ssRNA seq analysis the authors state "we identify Developing papillary fibroblasts as a transient cell population that is defined by Lef1 expression.", but this is not clear from the ssRNA seq analysis. In Figure 2—figure supplement 1, Lef1 expression seems to be largely excluded from cells within the Dpp4 expression cluster (cluster 2), and Dkk1 (Cluster 0), which define the major papillary FB clusters. Can the authors expand upon how the Velocity Analysis identifies different genes than overlaying relative expression levels on the UMAPS?We thank the reviewer for allowing us to address this point. In the manuscript, we have discovered heterogeneity within neonatal papillary fibroblasts. We identified a population that express Lef1 and Dkk1  different from the CD26+ fibroblasts.RNA velocity computes the velocity trajectories of cells in scRNA-seq experiment using the unspliced/spliced ratio of mRNA of different genes across multiple cells. The ranked list of driver genes defined by RNA velocity represented the top genes that drive the calculated trajectories for each cluster. These genes are found based on the transcriptional splicing kinetic and are different from the relative expression level.3) Surrounding the claim of a transient papillary fibroblast population (which is an important part in their paper), several parts are unclear;We thank the reviewer for this comment and try to address this as follows. We want to make clear that ‘transient papillary fibroblast populations’ refers to the population of papillary fibroblasts found only in Developing skin between P0 and P7 . These fibroblasts express high levels of Lef1 and Dkk1 and low levels of Dpp4/CD26 .I.e. they could/should explore the fibroblast populations of all conditions to compare regeneration vs. scaring and regeneration vs. development .We have now done this. This part of the new Figure 2—figure supplement 2. We did not detect Dkk1 and Lef1 positive papillary fibroblast populations in any condition besides Developing skin.Which of the two papillary fibroblast population(s) is/are transient? How to explain the rather minor overlap of Lef1 expression with these two papillary fib populations? Where are the two populations in situ in developing and in regenerating skin?The transient population of papillary fibroblasts express Lef1 with a low level of Dkk1 with low levels of CD26. We have confirmed the location and the timepoint of this population by Immunofluorescent staining in Figure 2I-O. These fibroblasts located in the upper most region of the dermis and can only be found in Developing skin.4) Given that the WIHN generates a significant amount of cysts, the authors have to down-tone their statement of "without adverse phenotype". As the authors also refer to Hedgehog-pathway induced de novo HF formation (a model giving rise to tumors and new HFs), they likely meant that their model does not induce apparent tumors (the cysts look different compared to the obvious BCC-like lesions trough Hh-pathway activation) – however the authors totally neglect the fact (don't mention) that the mice apparently develop cysts in addition to HFs in wounds.Figure 5E, G, J. The regenerated HFs appear very abnormal and cyst-like. The authors state several times in the paper that Lef1 overexpression enhances regeneration without other adverse phenotypes, but these regenerated structure are very abnormal. Are they cancerous? P90 wounds appear to generate a significant amount of cysts; is this representative for all conditions or something more specific for the P90 timepoint?We thank the reviewer for this suggestion and have edited the manuscript as suggested. Regarding the cancerous potential of the cysts, we did not fully study the phenotypes of the cysts and hope that our toned down comments will leave this area of research for future studies.


Pseudomonas aeruginosa that acquired increasing levels of antimicrobial resistance (AMR) in response to treatment. Metagenomic analysis revealed the AMR genotype, while immunological analysis revealed massive and escalating levels of T-cell activation. These were both SARS-CoV-2 and P. aeruginosa specific, and bystander activated, which may have contributed to this patient’s persistent symptoms and radiological changes.Here, we describe the case of a COVID-19 patient who developed recurring ventilator-associated pneumonia caused by  The COVID-19 pandemic has brought with it the largest ever cohort of patients requiring mechanical ventilation. Complications associated with such severe viral infections are many-fold, and include increased susceptibility to secondary bacterial infections , as wellThe DISCOVER study  was established in March 2020 to collect and analyse longitudinal samples from COVID-19 patients. One study participant, an otherwise healthy male between 45 and 55 years of age presented to hospital with Type-1 respiratory failure (hypoxaemia), 20 days after he tested positive for SARS-CoV-2 by RT-PCR. At the time of testing he was asymptomatic , and this represents Day one on the time-line presented in Once admitted to our intensive care unit he was assessed, as all our patients are daily, for signs of additional infection through a process led by a consultant medical microbiologist along with senior pharmacist. At these meetings, the clinical status of the patient, radiological features, oxygen requirements, inflammatory indices  and any culture results are discussed. We had no concerns at the time of admission of this patient to the ICU that he had any infection other than that of SARS-CoV-2. Computerised tomography (CT) scans of the patient were collected through his time in the ICU and the classic features of COVID-19, including ground-glass opacities, were evident throughout .Pseudomonas aeruginosa strain was cultured from an aspirate collected from his endotracheal tube  >16 mg/l). He was prescribed a seven-day course of meropenem (1 g every 8 hr) and showed signs of clinical improvement. There were no further concerns about a bacterial infection during his ICU stay , although a third P. aeruginosa was cultured from a sample (ETT-3) collected two days after he completed his course of meropenem that was resistant to both pip/taz and meropenem (MICs > 16 mg/l and >8 mg/l respectively). His health continued to improve, and he was discharged to the respiratory ward a week later. The patient attended a follow-up clinic 3 weeks after hospital discharge where he reported on-going symptoms such as breathlessness and myalgia, and there was a significant drop in his oxygen saturations after mild exertion to 84%. Eight months following his positive test he is still reporting breathlessness and fatigue, common symptoms of the newly defined ‘Long COVID’ condition.After a week in the ICU he was diagnosed with ventilator-associated pneumonia (VAP) based on the clinical, radiological, biochemical, and microbiological parameters described above. An antibiotic susceptible e ETT-1, ,  in efflux and porin genes that affect the passage of the antibiotic into and out of the bacterial cell  in the DNA-binding domain of the MexR protein, that would likely result in the de-repression of this efflux system ; as well as an immunodominant human Cytomegalovirus protein (HCMV pp65) as an indication of non-T-cell receptor (TCR) driven bystander activation. This was followed by intracellular cytokine staining to detect production of IFN-γ and TNF-α by the specific T cells. Following the encounter with specific peptides we observed a robust CD4+ T-cell response to SARS-CoV-2 which decreased from day 23 to day 58, and a more modest SARS-CoV-2-specific CD8+ T-cell response. This is in line with published work, suggesting higher magnitudes of SARS-CoV-2-specific CD4+ versus CD8+ T-cells in severe COVID-19 patients , a single centre prospective study recruiting consecutive patients admitted with COVID-19, from 30.03.2020 until present . Blood/serum samples from pre-pandemic healthy controls and asymptomatic healthy controls were obtained under the Bristol Biobank .All ETT samples were processed in the Severn Infection Services laboratory as per standard operating procedures. Antibiotic susceptibility testing was performed by either disk diffusion  with 1 μg DNA starting input as per manufacture’s protocol. Briefly 1 μg of DNA was end repaired and a tailed using NEBNext Ultra II module E7546 . This was incubated at 20°C for 5 min followed by 65°C for 5 min. Clean-up was performed using AMPure XP beads (Beckman Coulter) in a 1X ratio. Adaptors were ligated by adding 5 μl adaptor mix (Oxford Nanopore) 25 μl ligation buffer (Oxford Nanopore) and 10 μl Quick T4 ligase (NEB Module MO202). Following a 20 min incubation at room temperature the adaptor ligated DNA was cleaned using AMPure beads in a 0.8 X ratio and washed using Long Fragment Buffer (Oxford Nanopore) before eluting in 25 μl of elution buffer (Oxford Nanopore). Final quantification by fluorometry (Qubit) was performed and 300 ng DNA prepared for sequencing according to the manufacturer’s instructions (Oxford Nanopore). Sequencing was performed on a PromethION R9.4.1 flow cell (FLO-PRO002) and run for 48 hr using live basecalling, files were outputted in Fast5 and Fastq format. Human-filtered sequencing data for this study have been deposited in the European Nucleotide Archive (ENA) at EMBL-EBI under accession PRJEB40239.https://github.com/SamStudio8/reticulatus/P. aeruginosa contigs for ETT-1 and ETT-3 was determined using Mauve .15-mer peptides overlapping by 10 amino acids and spanning the sequences of SARS-CoV-2 spike  and HCMV pp65 (AD169 strain) were purchased from Mimotopes . The purity of the peptides was >80% (Spike) or >70% (pp65) and peptides were dissolved as described previously . SARS-CoPBMCs were thawed and either stained ex vivo or stimulated in AIMV 2% FCS with or without peptide pools from SARS-CoV2 spike, M, N, HCMV pp65 , OrpF PA (10 μg/ml) or with PMA/iono  for 5 hr at 37°C in the presence of brefeldin A . To assess degranulation, CD107a FITC antibody was added to the cells at the beginning of the stimulation. Cells were stained with a viability dye Zombie Aqua (Biolegend) for 10 min at room temperature and with antibodies targeting surface markers  1% BSA (Sigma Aldrich)). Cells were fixed for 45 min/overnight in eBioscience Foxp3/Transcription factor fixation/permeabilization buffer (Invitrogen) and intracellular staining was performed using eBioscience Foxp3/Transcription factor permeabilization buffer (Invitrogen) for Ki67 or intracellular cytokines (30 min on ice). Cells were acquired on a BD Fortessa X20 and data analysed using FlowJo software v10.7. A complete list of antibodies is included in Pseudomonas Aeruginosa: The PA antigen OprF was diluted in coating buffer, added to the wells of MaxiSorp flat-bottom 96-Well immunoplates  and incubated for 2 hr at 37°C. Immunoplates were blocked with 1% BSA/PBS for 1 hr at 37°C. Sera from each sample were diluted and added to the immunoplates in triplicate and incubated at 4°C overnight. Biotin mouse anti-human IgG  was added to the plate and incubated for 1 hr at RT. Streptavidin-HRP  was added and incubated for 30 mins at RT. ELISAs were developed using TMB substrate. Results were recorded using a Multiskan GO Microplate Spectrophotometer  and absorbance values (OD 450) were converted to ELISA units. OprF antigen was produced using the recombinant vector pSUMO-OprF as described previously  were coated with either 10 mg/ml Spike or 20 mg/ml N protein in PBS and left overnight at 4°C followed by blocking for 1 hr (3% BSA/0.1% Tween/PBS). Dilution buffer (1% BSA/0.1% Tween/PBS) containing patient plasma samples collected at different time points, or serum controls, were added to wells either in duplicate  or pooled serum standard (PS)) or in single wells  at a final dilution of 1 in 450 (adjusting for dilution of plasma if obtained via PBMC collection) and left for 2 hr at RT. Goat anti-human IgG-HRP (Southern Biotech) was added at 1 in 25,000 in dilution buffer for 1 hr, followed by development with OPD solution (Sigma) as per the manufacturer’s instructions. Development was quenched after 30 min using 3M HCl and absorbance measured at 492 and 620 nm using a BMG FLUOstar Omega Spectrophotometer. Plots show mean and standard deviation where samples were run in duplicate.a. eviously . b. ELISeviously  with somControl samples: Serum from n = 6 adult pre-pandemic donors recruited in 2008 for a vaccine trial were obtained from the Bristol Biobank (NHS REC 14/WA/1253) and were used as known-negative controls on the same plate as the COVID19 case samples, in duplicate. In addition, we have included the OD values from the healthy control donor samples which were used as controls for the T cell assays; these donors were collected during the pandemic but reporting no exposure or symptoms prior to sampling . These samples were run in single wells on different plates to the COVID19 case samples; however, all plates included a pooled serum (PS) standard control, in duplicate, to assess for inter-plate variability. The PS average ODs across six plates are therefore shown. The PS, HC and PP samples used in this experiment were heat inactivated at 56°C for 30 min, while the patient plasma were not (after testing negative for SARS-CoV-2). Despite the difference in sample type and handling, we are confident these do not impact on antibody levels or ELISA signal from our own in-house comparisons (data not shown) as well as data from others . In the interests of transparency, eLife publishes the most substantive revision requests and the accompanying author responses.Acceptance summary:The article demonstrates the capacity of multidisciplinary technologies to provide illustrative insights into hitherto hidden aspects of the evolution of immune responses during a complicated SARS-CoV2 infection and recovery. In particular, the prominent bystander T cell activation in hospital and escalating number of circulating activated T-cells more than two months after testing positive for SARS-CoV-2, and six weeks after clearing the viral infection are notable. It is unusual to get this level of detail, albeit for a single patient, and hopefully this would lead to further thinking and research about how to approach and treat patients with long COVID.Decision letter after peer review:[Editors’ note: the authors submitted for reconsideration following the decision after peer review. What follows is the decision letter after the first round of review.]eLife. Your submission has been assessed by a Senior Editor in consultation with a member of the Board of Reviewing Editors. Although the work is of interest, we regret to inform you that the findings at this stage are too preliminary for further consideration at eLife.Thank you for choosing to send your work, "Post-acute COVID-19 associated with evidence of bystander T-cell activation and a recurring AMR bacterial pneumonia", for consideration at Specifically, the major conclusion, namely bystander T cell activation in severe COVID19, even though plausible, is not justified from the data presented in the manuscript. Even with the short form assessment, the manuscript would require significant amount of additional data from multiple patients of different severity and co-infection patterns to make any claims on the finding of bystander activation.Reviewer #1:P. aeruginosa co-infection with persistent T cell activation, mostly of a bystander nature. While the Pseudomonasaeruginosa strain was initially found to be antibiotic sensitive and treated accordingly, within eight days the bacterial infection re-emerged. Whole genome sequencing revealed a mixed infection of P. aeruginosa associated with AMR infections and a coagulase negative S. haemolyticus strain. The authors profiled activation status of monocytes and T cells during the course of the hospitalization of the patient. By profiling antigen specific responses, they identified that a large proportion of activated T cells that neither recognized SARS-CoV2 nor P. aeruginosa antigens. Responses to HCMV were evident in the patient. Such bystander T cell responses are known in other viral infections also, although the relevance of these is not well understood.Gregarova et al., present a clinical case of COVID-19 and ventilator acquired 1) This study uses elegant molecular tools to quantify T cell responses in the patient. The finding that there is an increase in activated bystander T cells during the course of the disease may be important. The authors make an important point about the relevance of this finding to potential use of corticosteroids in treatment of severe COVID19. However, this study does not have the power to inform whether ventilator acquired co-infections are the drivers of this bystander activated state in COVID19 patients. A larger study with defined groups of SARS-CoV2 with and without VAP infection, and VAP infections without SARS-CoV2 infection would be required to evaluate the relevance of the bystander T cell response in COVID19 disease severity/outcome.Reviewer #2:Pseudomonas aeruginosa evident with bystander T cell activation. The case study demonstrates the potential application of multidisciplinary technologies to longitudinally collected patient samples to define the complex dynamics of patient-pathogen-therapy interactions in real-time. Though the importance and novelty of the timely research, the lack of appropriate sample size in the key experiment limits the overall significance of this work.The manuscript by Gregorova et al., investigates a COVID-19 patient with an antibiotic-resistant secondary bacterial infection by 1) This is a practical matter, but a significant one. How confident are the authors to claim any statement from a single patient case study? Some of the immune cell response data look dramatic. However, with only one data point, no biological replicates and no possible statistics is not very convincing.2) It's unclear how the authors chose and prepared the controls, the "pre-pandemic healthy controls" and "asymptomatic healthy controls" are not well explained. And this part of immune assay is not clearly documented while this is critical, like are they undergone the same treatment, and what are the vital statistics?P. aeruginosa is associated with the disease severity or pneumonia. One of such confusing statement is "There were no further concerns about a bacterial infection during his ICU stay although a third P. aeruginosa was cultured from a sample (ETT- 3) collected two days after he completed his course of meropenem, that was resistant to both pip/taz and meropenem (MICs >16 mg/l and >8mg/l respectively)" in the Introduction. Does this mean in ETT-3, this bacterium is still detected and resistant to antibiotics? But why it becomes not a concern? If it's because the patient is in his remission stage, it makes people wonder if the earlier concern from the bacterial infection during ETT-1 and ETT-2 is a side effect from the severe SARS-CoV2 symptoms instead of any causation or association effects.3) It's not clear how the presence of P. aeruginosa after the patient is discharged from hospital and even before the development of SARS-CoV-2? Although it's too late to ask such a question about the level before SARS-CoV-2, is it possible that P. aeruginosa is an existing bacterium in this patient other than from a secondary bacterial infection after SARS-CoV-2?4) How's the level of 5) What is the logic of performing sequencing on ETT-1 and ETT-3 but not ETT-2? ETT-2 genome sequencing might help to show some evidence of evolution of the mutation points.6) During metagenomics, did the authors see other microbes? It's surprising if there are only two bacterial species detected in those samples using metagenomic sequencing. Or is it because these two strains are the most dominant ones that detected? If so, it would be useful to show the whole microbial community profile from this sequencing.Staphylococcus haemolyticus is "not recognized as lung pathogens" as stated by the authors, if this particular strain is resistant to methicillin, would it also be a potential target strain with AMR deteriorating the disease in this scenario? Did the authors also detect it from ETT-3? Would it be necessary for the authors to carry out a similar assay as Figure 3E and f using the S. haemolyticus antigen to show if it has an effect?7) Since there are two strains that are fully sequenced, although +, CD8+ and TCR-gd T-cells appear to wane between days 23-28 and boosted after day 28, is there an antibiotic effect here as pip/taz was administrated ~day 28? How to explain a decrease around day 45 on Figure 3B? Was that also an antibiotic effect by the starting of meropenem? It could be further discussed in the paper. And authors should explain a little more in the text about the difference between Figure 3A and 3B.8) It's very interesting observation that CD4Reviewer #3:P. aeruginosa encoding antibiotic resistance. The fundamental thrust of the paper is the inference that both the initial respiratory failure and the subsequent VAP episodes result directly or indirectly from immunopathology driven by bystander T cell activation, which the investigators assess by determining CD4 and CD8 cell cytokine expression following PBMCs exposure to viral and bacterial peptides.Dr Gregorova and colleagues present an interesting case report entitled "Post-acute COVID-19 associated with evidence of bystander T-cell activation and a recurring antibiotic-resistant bacterial pneumonia." The report details a patient that presented with respiratory failure 20 days after testing positive for COVID-19 on screening following exposure to a family member. The patient's course was complicated by two episodes of VAP with metagenomics serially revealing complete genomes of The report is easy to read and proposes an explanation for the patient's respiratory failure that is congruent with known immune responses to SARS-CoV-2. Indeed, as the authors note, this may help explain the observed efficacy of dexamethasone in patients with respiratory insufficiency. However, there are limitations that reduce enthusiasm.P. aeruginosa sensing/responding/clearance by any cell population.1) The paper broadly suggests/implies that bystander activation of T cells is a proximate cause of the VAP episodes without any direct evidence to support this notion. It is well established in the literature that post-viral leukocyte dysfunction (most often lymphocytes and monocyte/macrophage lineage cells) enhance susceptibility to secondary bacterial infections. In this case, the authors demonstrate variably elevated numbers of T cells but do not demonstrate failures of 2) The essential arguments for bystander activation are the stimulation experiments in Figure 3E-F. These data are widely variable and are difficult to interpret in the absence of data from the times that VAP was first suspected. The only shown dates are from ICU admission and two dates each after several days of VAP therapy.3) In a single case report, it is always challenging to confidently know what is driving an observed immune response. This is particularly so in a patient who was well at the time of viral diagnosis but presents 20 days later. Certainly, the authors' inference that the respiratory failure represents COVID-19 immunopathology is plausible, even likely. However, since the interval between diagnosis and respiratory failure is longer than the mean interval reported in recent large series and since longer intervals provide more opportunities for patients to acquire new pathogens/be exposed to new insults, more robust evidence than a single case would typically be expected to make such a claim.P. aeruginosa during a single episode of critical illness is unsurprising. As above, there seems to be an underlying implication that the T cell activation drives the SNP differences between the isolates, but that is not further demonstrated. Metagenomic assessment at the time of ICU admission might have been supportive of the authors' assessment that there was no active viral infection (SARS-CoV-2 or otherwise) driving the acute decompensation that led to intubation.4) The metagenomics data are impressively generated, but don't drive new understanding. That an intubated patient might acquire two related strains of eLife.Thank you for your note appealing the decision on your article "Post-acute COVID-19 associated with evidence of bystander T-cell activation and a recurring AMR bacterial pneumonia" for reconsideration by We would like to assure you that the single case did not underscore rejection. We do consider case reports if they change the practice of medicine, bring to the fore important clinical questions and/or trigger new patient-centered research. Your report fell into the first category. With that said, there were significant concerns that I have listed below in consultation with the Reviewing Editor who handled your paper, and we would be happy to send it out for re-review, without a guarantee of acceptance, once we receive a point-to-point response to the critique in the reviews that were sent to you previously.Specifically, we would consider a rebuttal that focuses on the comments of reviewer 3 and broadly answers the summarised concerns listed below. This may be done through additional clinical data and experimental data that the authors find feasible.The case study's value is in suggesting that bystander T cell activation in SARS-CoV2 infection may have led to a severe COVID-19 presentation. This supports the benefit of corticosteroids in COVID-19. The message is indeed plausible and important. The authors need to tell us how much it adds to what we know .The essence of the case report seems to be that a patient with asymptomatic SARS CoV2 infection developed respiratory symptoms suggestive of COVID19 at 2 weeks post-infection, requiring hospitalisation. After more than 96 hrs of hospitalisation the patient required ICU admission and was SARS CoV2 negative, but resistant P. Aeurginosa positive on ETT aspirate. At this point bystander T cell activation was noted. The authors link the bystander activation to the SARS-CoV2 infection and disease progression, which is plausible but uncertain due to questions: namely (a) whether an additional infection may have occurred in 2 weeks, (b) whether bystander activation measured at 3 weeks is confidently determined and relatable to original infection, and (c) whether the hospital-acquired multi drug resistant pneumonia is related to the immune dysfunction.The specific concerns that need to be considered and addressed are:a) Is this severe COVID-19 or a new insult given that 15 days passed from PCR positivity for onset of symptoms? A clear comparison of this to reported intervals between onset of infection and clinical deterioration would help make the case stronger. If this is very unusual, then alternative explanations, such as a new infection, become more likely than severe COVID-19. Clinical data would be helpful, including any repeat PCR at admission.P. aeruginosa infection is probably hospital-acquired and multiple strains are quite possible. The link to bystander cell activation only arises if it led to ineffectual sensing/clearance. Can this be supported by any experimental evidence beyond clinical deterioration?b) c) The essential arguments for bystander activation are illustrated in Figure 3E-F – that were found not to be particularly convincing. At the very least, please provide full data and experimental replicates. [Editors’ note: The authors appealed the original decision. What follows is the authors’ response to the first round of review.]Reviewer #1:P. aeruginosa co-infection with persistent T cell activation, mostly of a bystander nature. While the Pseudomonas aeruginosa strain was initially found to be antibiotic sensitive and treated accordingly, within eight days the bacterial infection re-emerged. Whole genome sequencing revealed a mixed infection of P. aeruginosa associated with AMR infections and a coagulase negative S. haemolyticus strain. The authors profiled activation status of monocytes and T cells during the course of the hospitalization of the patient. By profiling antigen specific responses, they identified that a large proportion of activated T cells that neither recognized SARS-CoV2 nor P. aeruginosa antigens. Responses to HCMV were evident in the patient. Such bystander T cell responses are known in other viral infections also, although the relevance of these is not well understood.Gregarova et al., present a clinical case of COVID-19 and ventilator acquired 1) This study uses elegant molecular tools to quantify T cell responses in the patient. The finding that there is an increase in activated bystander T cells during the course of the disease may be important. The authors make an important point about the relevance of this finding to potential use of corticosteroids in treatment of severe COVID19. However, this study does not have the power to inform whether ventilator acquired co-infections are the drivers of this bystander activated state in COVID19 patients. A larger study with defined groups of SARS-CoV2 with and without VAP infection, and VAP infections without SARS-CoV2 infection would be required to evaluate the relevance of the bystander T cell response in COVID19 disease severity/outcome.We are in absolute agreement with this reviewer on this matter. As an entirely descriptive case study of a single patient, and we make no statements within the manuscript as to there being a causal link between the VAP and the bystander activation observed. However, if the reviewer feels this has been inadvertently inferred anywhere within the manuscript, we would be more than happy to address this.eLife if they “change the practice of medicine, bring to the fore important clinical questions and/or trigger new patient-centred research”. With this in mind we hope the reviewer will find themselves in agreement with us that our study satisfies this remit in that, just as they suggest, a study of a wider population of patients is warranted based on these findings.As discussed above, the editor has confirmed that case studies are considered suitable for publication in Reviewer #2:Pseudomonas aeruginosa evident with bystander T cell activation. The case study demonstrates the potential application of multidisciplinary technologies to longitudinally collected patient samples to define the complex dynamics of patient-pathogen-therapy interactions in real-time. Though the importance and novelty of the timely research, the lack of appropriate sample size in the key experiment limits the overall significance of this work.The manuscript by Gregorova et al., investigates a COVID-19 patient with an antibiotic-resistant secondary bacterial infection by eLife if they “change the practice of medicine, bring to the fore important clinical questions and/or trigger new patient-centred research”. With this in mind we hope the reviewer will find themselves in agreement with us that our study satisfies this remit in that it is an interesting study that raises important clinical questions and warrants further investigation in a wider cohort of patients. We will address the specific issue raised with regards to replicates below.This is an entirely descriptive case study of a single patient. As discussed above, the editor has confirmed that these types of studies are considered suitable for publication in 1) This is a practical matter, but a significant one. How confident are the authors to claim any statement from a single patient case study? Some of the immune cell response data look dramatic. However, with only one data point, no biological replicates and no possible statistics is not very convincing.We are in complete agreement with the reviewers that no statement can be made with any confidence based on the findings from a single patient, which is why we were careful not to make any. We have re-read the manuscript to ensure this remains the case, however if the reviewer can point us to any, we may have inadvertently written we will happily temper them.The issue with regards to biological replicates in a case study of a severely ill patient is complex. Biological replicates for larger immunological studies would typically include samples from multiple patients, which is beyond the remit of a case study as we were limited by the numbers of samples we could collect for research purposes. However, with what we were able to obtain, our immunophenotyping was performed on PBMCs from five longitudinal time points  while intracellular cytokine staining was performed on 3 time points  due to limiting cell numbers. For this revised manuscript we now provide technical replicates for the experiments described in the original manuscript consistent . We also provide new data (in duplicate) strengthening the case for the bystander activation we have observed for this patient . We hope this is sufficient to alleviate the reviewers concerns on this matter.2) It's unclear how the authors chose and prepared the controls, the "pre-pandemic healthy controls" and "asymptomatic healthy controls" are not well explained. And this part of immune assay is not clearly documented while this is critical, like are they undergone the same treatment, and what are the vital statistics?We thank the reviewer for pointing out this omission in the original manuscript. Details on the pre-pandemic and asymptomatic healthy controls and a more detailed description of the methodology for the serology assay have been included . These are copied below for your reference:“ELISA methods were based on the protocols for measuring SARS-CoV-2 seroconversion outlined in Amanat et al., (2020) and Stadlbauer et al., (2020) with modifications. […] Despite the difference in sample type and handling, we are confident these do not impact on antibody levels or ELISA signal from our own in-house comparisons (data not shown) as well as data from others .”P. aeruginosa is associated with the disease severity or pneumonia. One of such confusing statement is "There were no further concerns about a bacterial infection during his ICU stay although a third P. aeruginosa was cultured from a sample (ETT- 3) collected two days after he completed his course of meropenem, that was resistant to both pip/taz and meropenem (MICs >16 mg/l and >8mg/l respectively)" in the Introduction. Does this mean in ETT-3, this bacterium is still detected and resistant to antibiotics? But why it becomes not a concern? If it's because the patient is in his remission stage, it makes people wonder if the earlier concern from the bacterial infection during ETT-1 and ETT-2 is a side effect from the severe SARS-CoV2 symptoms instead of any causation or association effects.3) It's not clear how the presence of The diagnosis of VAP in intubated patients is complex. In our intensive care unit, there is a daily infection review led by the Consultant Medical Microbiologist along with a senior Pharmacist. At these meetings, the clinical progress of all patients, inflammatory indices  and the relevance of concurrently cultured isolates is discussed. For this patient, the initial samples ETT-1 and ETT-2 coincided with an increasing oxygen requirement, fever, and the patient becoming more clinically unwell, and therefore a clinical diagnosis of likely VAP was made and patient was treated with antibiotics for same. At the time of ETT-3, the patient was clinically well and did not meet any clinical diagnostic criteria for VAP, so this was not deemed significant. We explain this in greater detail in the revised manuscript (Introduction).P. aeruginosa after the patient is discharged from hospital and even before the development of SARS-CoV-2? Although it's too late to ask such a question about the level before SARS-CoV-2, is it possible that P. aeruginosa is an existing bacterium in this patient other than from a secondary bacterial infection after SARS-CoV-2?4) How's the level of P. aeruginosa is a ubiquitous environmental bacteria, and while it can be found as a commensal in the respiratory tract of some individuals, this is typically only when they have some underlying chronic suppurative lung disease such as bronchiectasis. Prior to his COVID-19 diagnosis this relatively young patient was healthy with no prior medical issues, which makes us think it is more likely the positive cultures and metagenomic data represent hospital or ICU acquired colonisation and subsequent infection of this patient. We have made a comment to explain this in the manuscript (Results section).Measuring levels of bacterial load in VAP is extremely difficult and not routinely done in clinical practice. 5) What is the logic of performing sequencing on ETT-1 and ETT-3 but not ETT-2? ETT-2 genome sequencing might help to show some evidence of evolution of the mutation points.There is no logic to this, just an unfortunate situation that arose due to the pressures the diagnostic lab was under during the first wave of the pandemic. ETT-2 was not made available for research and likely disposed of in error, and this has been explaining in the revised manuscript (Results section).6) During metagenomics, did the authors see other microbes? It's surprising if there are only two bacterial species detected in those samples using metagenomic sequencing. Or is it because these two strains are the most dominant ones that detected? If so, it would be useful to show the whole microbial community profile from this sequencing.In the original manuscript we only reported the whole genomes we were able sequence from the clinical samples. However, as correctly pointed out by the reviewer, the omission of information on what other organisms were present is unhelpful. In the revised manuscript we now described these data .7) Since there are two strains that are fully sequenced, although Staphylococcus haemolyticus is "not recognized as lung pathogens" as stated by the authors, if this particular strain is resistant to methicillin, would it also be a potential target strain with AMR deteriorating the disease in this scenario?S. haemolyticus genome we originally reported as being part of ETT-1 was in fact part of ETT-3. Given the relatively healthy status of the patient at the time ETT-3 was collected and the likelihood that it was a commensal as opposed to an infecting organism, we have removed specific mention of this from the revised manuscript. Instead, we report its presence as part of the microbial make-up of ETT-3 in Figure 2B.Having revisited our metagenomic data we found a labelling error such that the Did the authors also detect it from ETT-3? Would it be necessary for the authors to carry out a similar assay as Figure 3E and f using the S. haemolyticus antigen to show if it has an effect?S. haemolyticus genome we originally reported as being part of ETT-1 was in fact part of ETT-3. In the revised manuscript we now include greater details on the microbial composition of both ETT-1 and ETT-3, where the only bacterial DNA found in ETT-1 was that of the infecting P. aerunginosa strains; whereas ETT-3, where the patient had recovered from his VAP there was greater microbial diversity, including the S. haemolyticus strain. As such we don’t believe it to be necessary to perform ICS experiment with a S. haemolyticus antigen.As mentioned above, when we revisited our metagenomic data we found a labelling error such that the +, CD8+ and TCR-gd T-cells appear to wane between days 23-28 and boosted after day 28, is there an antibiotic effect here as pip/taz was administrated ~day 28? How to explain a decrease around day 45 on Figure 3B? Was that also an antibiotic effect by the starting of meropenem? It could be further discussed in the paper. And authors should explain a little more in the text about the difference between Figure 3A and 3B.8) It's very interesting observation that CD4+ and gd T-cells) but as this was not observed for the other cells type studied, we feel it is too speculative to bring into this descriptive study.The initial waning of T-cell activation and proliferation shown in Figure 3E-F could suggest a declining response to a viral infection, which would be in line with another case report that looked at T cell kinetics longitudinally in a COVID-19 patient and shows that T-cell activation during SARS-CoV-2 infection declines from around 20 days post-infection . While there is some evidence that antibiotics can interact with aspects of host immunity, the available data suggests the activity is typically suppressive. With this in mind, we feel the increase in activity that coincided with the administration of pip/taz is more likely due to the response of the immune system to the VAP. Regarding the decrease following meropenem treatment, it is possible it plays a roll in the observed decrease in proliferation of some of the cell types we studied  The paper broadly suggests/implies that bystander activation of T cells is a proximate cause of the VAP episodes without any direct evidence to support this notion. It is well established in the literature that post-viral leukocyte dysfunction (most often lymphocytes and monocyte/macrophage lineage cells) enhance susceptibility to secondary bacterial infections. In this case, the authors demonstrate variably elevated numbers of T cells but do not demonstrate failures of As this is a case study with a single patient, we were very careful not to make any statements or infer any specific thoughts we had on what has happened with this patient. It’s always possible that such inferences slip in inadvertently, and if the reviewer can direct us to where these are to be found we will modify/temper that language used.It is interesting that the reviewer felt we were inferring the bystander activation was a proximate cause of the VAP, as we believe the opposite is more likely to be true. With or without prior viral infection, the mechanical ventilation of patients leaves them highly susceptible, such that between 10 and 30% will typically succumb to a bacterial VAP, and this patient has fallen into this category. If we were pushed to make a statement on what we believe might be going on (given the limitation of a single patient) it’s that the onslaught of an invasive bacterial infection immediately after the viral infection (and the heightened and prolonged immune response this triggered) is responsible for the observed bystander activation. This activation may be responsible for the ongoing inflammatory associated problems that patient is experiencing, but again, we believe we have been very careful not to be explicit about this in the manuscript, give its limitation as a case study.P. aerunginosa, we make no comments or assertion as to their role in the clearance of the VAPs, as in both cases the patient was treated with appropriate antibiotics, which will have had a dominant affect on clearing these infections.It is worth noting here that although we detect both an antibody and T-cell response specific to 2) The essential arguments for bystander activation are the stimulation experiments in Figure 3E-F. These data are widely variable and are difficult to interpret in the absence of data from the times that VAP was first suspected. The only shown dates are from ICU admission and two dates each after several days of VAP therapy.+T cells are activated and proliferating in line with other studies on bystander activation, showing increased expression of activation and proliferation markers by CMV-specific CD8+ cells when compared to the CMV-specific CD4+ cells. We also found that the CD8+ CMV-specific T cells were predominantly TEMRA and TEM cells while CD4+ CMV-specific T cells were predominantly TEM cells , which is in line with previous reports on this phenomenon.Unfortunately, we were unable to perform T-cell stimulation and ICS on samples from all time points from this patient, due to the limited blood samples that we could ethically collect from a severly ill patient. As explained above, we have repeated the T-cell stimulation with CMV and SARS-CoV-2 spike peptides on the last vial of PBMCs made available to us, and we now also include data (in duplicate) on the T cell response to both CMV and SARS-CoV-2 . We were also able to measure the expression of activating and proliferating markers on CMV-specific T cells and show that CMV-specific CD83) In a single case report, it is always challenging to confidently know what is driving an observed immune response. This is particularly so in a patient who was well at the time of viral diagnosis but presents 20 days later. Certainly, the authors' inference that the respiratory failure represents COVID-19 immunopathology is plausible, even likely. However, since the interval between diagnosis and respiratory failure is longer than the mean interval reported in recent large series and since longer intervals provide more opportunities for patients to acquire new pathogens/be exposed to new insults, more robust evidence than a single case would typically be expected to make such a claim.As discussed above, we were careful not to make any claims in relation to what is driving the observed immune response, given the limitation of the study. However, if the reviewer can point us to where these are inferred we will be more than happy to address/temper these.We are however confident that the SARs-CoV-2 infection was responsible for this patient’s respiratory failure. There was a gap of 13 days from this patient testing positive to the development of symptoms, and a further week before his symptoms became such that he needed hospitalisation. The CDC, based on the findings of several studies, advise that the incubation period for COVID-19 can be as long as 14 days, which is a day longer than that experienced by this patient. .Also, although the patient tested negative for SARs-CoV-2 upon admission, none of his cultures up until ETT-1 grew anything to suggest a secondary infection. He also he had no other clinical features prior to the collection of ETT-1 to suggest any other clinical bases for his symptoms. The patient also had three sets CT scans take; upon admission to the ICU, when the first VAP was diagnosed and between his first and second VAP. The ground glass opacities typical of COVID-19 were evident throughout. These have now been included as supplementary data , as they are supportive of the fact that the patient required hospitalisation as a result of COVID-19.P. aeruginosa during a single episode of critical illness is unsurprising. As above, there seems to be an underlying implication that the T cell activation drives the SNP differences between the isolates, but that is not further demonstrated. Metagenomic assessment at the time of ICU admission might have been supportive of the authors' assessment that there was no active viral infection (SARS-CoV-2 or otherwise) driving the acute decompensation that led to intubation.4) The metagenomics data are impressively generated, but don't drive new understanding. That an intubated patient might acquire two related strains of As a study of a single patient, it’s difficult to say that what is presented drives any new understanding, but instead demonstrates the potential for what could be achieved/learned if applied to a wider cohort of patients. We include the metagenomics here as an illustration of what can be achieved above and beyond routine culture-based approaches, including the detection of AMR conferring mutations.P. aerunginosa with differing AMR profiles is impossible to say, but we discuss both of these scenarios in greater detail in the revised manuscript (Results section).We are again interested to see that the reviewer has concluded that we felt the T-cell activity was driving the SNPs in the strains. This isn’t the case at all, and if the section in the manuscript that led the reviewer to think this could be highlighted to us, we will address the language we used there. Instead, we believe it is far more likely that the antibiotics used to treat the VAPs led to the selection of the AMR strains. Whether it is one strain that acquires the mutations to become resistant, or sequential infections with a different strain of [Editors’ note: what follows is the authors’ response to the second round of review.]The case study's value is in suggesting that bystander T cell activation in SARS-CoV2 infection may have led to a severe COVID-19 presentation. This supports the benefit of corticosteroids in COVID-19. The message is indeed plausible and important. The authors need to tell us how much it adds to what we know .The Mathew et al., 2020 paper describes distinct immunophenotypes that associate with disease in 125 hospitalized COVID-19 patients at a single timepoint. There is information within that paper describing some COVID-19 patients that acquired secondary infections  but little information regarding the nature of the secondary infection, and only partial immunophenotyping for these patients is reported.Our current case report, which was submitted prior to publication of the Mathew et al., study, provides a detailed and in-depth longitudinal analysis of the kinetics of immune activation of conventional T cells, gd T cells and other immune cells during a secondary bacterial infection post COVID-19, albeit in a single patient. We also show evidence of bystander activation of T-cells, which was not examined in the Mathew et al., paper. In the revised manuscript we now discuss the parallels between our work and what was reported in the Mathew et al., paper (Results section and Discussion section).The essence of the case report seems to be that a patient with asymptomatic SARS CoV2 infection developed respiratory symptoms suggestive of COVID19 at 2 weeks post-infection, requiring hospitalisation. After more than 96 hrs of hospitalisation the patient required ICU admission and was SARS CoV2 negative, but resistant P. Aeurginosa positive on ETT aspirate. At this point bystander T cell activation was noted. The authors link the bystander activation to the SARS-CoV2 infection and disease progression, which is plausible but uncertain due to questions: namely (a) whether an additional infection may have occurred in 2 weeks, (b) whether bystander activation measured at 3 weeks is confidently determined and relatable to original infection, and (c) whether the hospital-acquired multi drug resistant pneumonia is related to the immune dysfunction.a) Is this severe COVID-19 or a new insult given that 15 days passed from PCR positivity for onset of symptoms? A clear comparison of this to reported intervals between onset of infection and clinical deterioration would help make the case stronger. If this is very unusual, then alternative explanations, such as a new infection, become more likely than severe COVID-19. Clinical data would be helpful, including any repeat PCR at admission.There were 13 days between the patient testing positive for SARS-CoV-2 and developing symptoms. Once admitted to our intensive care unit he was assessed, as all our patients are daily, for signs of additional infection through a process led by a consultant medical microbiologist along with senior pharmacist. At these meetings, the clinical status of the patient, inflammatory indices  and any culture results are discussed. We had no concerns at the time of admission of this patient to the ICU that he had any infection other than that of SARS-CoV-2. We agree that the time between him testing positive by RT-PCR and develop symptoms is atypical, however the CDC, based on the findings of several studies, advise that the incubation period for COVID-19 can be as long as 14 days, which is a day longer than that experienced by this patient. . We have discussed this in greater details within the revised manuscript (Introduction)With regards to additional clinical data, he was tested for SARS-CoV-2 upon admission to hospital as well as upon admission to the ICU the following day, both tests were negative. Until ETT-1, none of his cultures grew anything to suggest a secondary infection. The patient had three sets of CT scans take; upon admission to the ICU, when the first VAP was diagnosed and between his first and second VAP. The ground glass opacities typical of COVID-19 were evident throughout. These have now been included as supplementary data .P. aeruginosa infection is probably hospital-acquired and multiple strains are quite possible. The link to bystander cell activation only arises if it led to ineffectual sensing/clearance. Can this be supported by any experimental evidence beyond clinical deterioration?b) If we have understood this question correctly, we are being asked if we believe there to be a link between the clearance of the recurring VAPs and the observed bystander activation; and whether we have any additional experimental evidence to support this? While we provide additional data (described below) in support of the observed bystander activation, we have been careful not to make any causal links between what we have observed for this patient, except to propose that this massive level of immune activation may be contributing to his ongoing inflammatory-associated symptoms. With regards to clearance of the VAPs, having been treated with antibiotics, the effect of the immune system is likely to be minimal, so we believe it unlikely that the bystander activation contributed positively or negatively to this. We have ensured within the revised manuscript that this is made clearerc) The essential arguments for bystander activation are illustrated in Figure 3E-F – that were found not to be particularly convincing. At the very least, please provide full data and experimental replicates.+ and CD8+T cells within the sample. We also show new data that demonstrates (in duplicate) that these CMV-specific CD4+ and CD8+T cells were activated and proliferating, based on their expression of activation and proliferation markers, which supports that they are bystander activated  . The expression of activation and proliferation markers by CMV-specific CD8+T cells during an infection with an unrelated pathogen is in line with other studies on bystander activation, showing increased expression of activation and proliferation markers by CMV-specific CD8+ cells when compared to the CMV-specific CD4+ cells. We also found that the CD8+ CMV-specific T cells were predominantly TEMRA and TEM cells while CD4+ CMV-specific T cells were predominantly TEM cells , which is in line with previous reports on this phenomenon.As there are strict ethical constraints on how many blood samples can be collected from severely ill patients, we endeavoured throughout this study to make the best use of what we were able to obtain, which was what was presented in the original manuscript. However, we have since managed to obtain one final vial of PBMCs from this patient collected during his time in the ICU at day 38 post RT-PCR+ test. To address the concern raised here, we have used these cells to provide replicate data that shows the presence of CMV-specific CD4