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Farias Amorim et al. 2023

This is the R code associated with the manuscript:

Multi-omic profiling of cutaneous leishmaniasis infections reveals microbiota-driven mechanisms underlying disease severity

Camila Farias Amorim, Victoria M. Lovins, Tej Pratap Singh, Fernanda O. Novais, Jordan C. Harris, Alexsandro S. Lago, Lucas P. Carvalho, Edgar M. Carvalho, Daniel P. Beiting, Phillip Scott*, Elizabeth A. Grice*

Code for my publication "Multi-omic profiling of cutaneous leishmaniasis infections reveals microbiota-driven mechanisms underlying disease severity", 2023

[Science Translational Medicine, DOI: 10.1126/scitranslmed.adh1469](https://www.science.org/doi/full/10.1126/scitranslmed.adh1469)

Abstract

Leishmania braziliensis infection results in inflammation and skin injury, with highly variable and unpredictable clinical outcomes. Here, we investigated the potential impact of microbiota on infection-induced inflammatory responses and disease resolution by conducting an integrated analysis of the skin microbiome and host transcriptome on a cohort of 62 L. braziliensis-infected patients. We found that overall bacterial burden and microbiome configurations dominated with Staphylococcus spp. were associated with delayed healing and enhanced inflammatory responses, especially by IL-1 family members. Dual RNA-seq of human lesions revealed that high lesional S. aureus transcript abundance was associated with delayed healing and increased expression of IL-1β. This cytokine was critical for modulating disease outcome in L. braziliensis-infected mice colonized with S. aureus, as its neutralization reduced pathology and inflammation. These results implicate the microbiome in cutaneous leishmaniasis disease outcomes in humans and suggest host-directed therapies to mitigate the inflammatory consequences.

The locations of the core components of this repo are outlined in the file system map below. In short, there are the following main directories:

  • Public_submission - contains the main .Rscripts, main Robjects, tables, raw data associated this manuscript (with exception of raw sequencing files). The subdirectories included here are mostly divided per datasets or experiment (RNA-seq, 16S-seq, S. aureus isolates data, mice-experimental data, ...).

  • Amorim2022_SupplemmentalTable1_LeishOmics_StudyDesign.txt - Clinical metadata associated with the patients included in this study (n=62).

  • /Bacterial_isolates/ - Contains data about the live bacterial isolates collected from CL lesions. See isolation process and methodology in the official manuscript.

  • /Biopsy_qPCR/ - contains the raw data from the 2 qPCR experiments included in this manuscript: L. braziliensis's 18S and total bacteria's 16S ribosomal subunits. Ps.: In some parts there are still included the code for a failed qPCR trying to quantify specifically S. aureus. This experiment was never included in the manuscript.

  • /Integrative_Analysis/ - integration pipeline using the rexposome R package

  • /16S-seq/ - Data regarding the 16S-seq analyses performed with Qiime2 and final modeling in R.

  • /RNA-seq/ - Data regarding the RNA-seq dataset: from pre-processing, mapping with kallisto pseudoaligner, gene annotation and final modeling in R.

  • /Mice_experiments/ - Data regarding the experiments performed by Tej Singh. Here with blocked IL1-signaling in mice in the context of S. aureus co-infection.