Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection.
Background Leishmaniasis is a parasitic disease caused by the Leishmania protozoan affecting millions of people worldwide, especially in tropical and subtropical regions. The immune response involves the activation of various cells to eliminate the infection. Understanding the complex interplay betw...
Published in: | PLOS Neglected Tropical Diseases |
---|---|
Main Authors: | , , |
Format: | Article in Journal/Newspaper |
Language: | English |
Published: |
Public Library of Science (PLoS)
2024
|
Subjects: | |
Online Access: | https://doi.org/10.1371/journal.pntd.0011892 https://doaj.org/article/90292e6c34b44544a204cdf369c9853d |
id |
ftdoajarticles:oai:doaj.org/article:90292e6c34b44544a204cdf369c9853d |
---|---|
record_format |
openpolar |
spelling |
ftdoajarticles:oai:doaj.org/article:90292e6c34b44544a204cdf369c9853d 2024-02-27T08:38:17+00:00 Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection. Zahra Rezaei Ahmad Tahmasebi Bahman Pourabbas 2024-01-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0011892 https://doaj.org/article/90292e6c34b44544a204cdf369c9853d EN eng Public Library of Science (PLoS) https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0011892&type=printable https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0011892 https://doaj.org/article/90292e6c34b44544a204cdf369c9853d PLoS Neglected Tropical Diseases, Vol 18, Iss 1, p e0011892 (2024) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2024 ftdoajarticles https://doi.org/10.1371/journal.pntd.0011892 2024-01-28T02:21:28Z Background Leishmaniasis is a parasitic disease caused by the Leishmania protozoan affecting millions of people worldwide, especially in tropical and subtropical regions. The immune response involves the activation of various cells to eliminate the infection. Understanding the complex interplay between Leishmania and the host immune system is crucial for developing effective treatments against this disease. Methods This study collected extensive transcriptomic data from macrophages, dendritic, and NK cells exposed to Leishmania spp. Our objective was to determine the Leishmania-responsive genes in immune system cells by applying meta-analysis and feature selection algorithms, followed by co-expression analysis. Results As a result of meta-analysis, we discovered 703 differentially expressed genes (DEGs), primarily associated with the immune system and cellular metabolic processes. In addition, we have substantiated the significance of transcription factor families, such as bZIP and C2H2 ZF, in response to Leishmania infection. Furthermore, the feature selection techniques revealed the potential of two genes, namely G0S2 and CXCL8, as biomarkers and therapeutic targets for Leishmania infection. Lastly, our co-expression analysis has unveiled seven hub genes, including PFKFB3, DIAPH1, BSG, BIRC3, GOT2, EIF3H, and ATF3, chiefly related to signaling pathways. Conclusions These findings provide valuable insights into the molecular mechanisms underlying the response of immune system cells to Leishmania infection and offer novel potential targets for the therapeutic goals. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 18 1 e0011892 |
institution |
Open Polar |
collection |
Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 Zahra Rezaei Ahmad Tahmasebi Bahman Pourabbas Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
description |
Background Leishmaniasis is a parasitic disease caused by the Leishmania protozoan affecting millions of people worldwide, especially in tropical and subtropical regions. The immune response involves the activation of various cells to eliminate the infection. Understanding the complex interplay between Leishmania and the host immune system is crucial for developing effective treatments against this disease. Methods This study collected extensive transcriptomic data from macrophages, dendritic, and NK cells exposed to Leishmania spp. Our objective was to determine the Leishmania-responsive genes in immune system cells by applying meta-analysis and feature selection algorithms, followed by co-expression analysis. Results As a result of meta-analysis, we discovered 703 differentially expressed genes (DEGs), primarily associated with the immune system and cellular metabolic processes. In addition, we have substantiated the significance of transcription factor families, such as bZIP and C2H2 ZF, in response to Leishmania infection. Furthermore, the feature selection techniques revealed the potential of two genes, namely G0S2 and CXCL8, as biomarkers and therapeutic targets for Leishmania infection. Lastly, our co-expression analysis has unveiled seven hub genes, including PFKFB3, DIAPH1, BSG, BIRC3, GOT2, EIF3H, and ATF3, chiefly related to signaling pathways. Conclusions These findings provide valuable insights into the molecular mechanisms underlying the response of immune system cells to Leishmania infection and offer novel potential targets for the therapeutic goals. |
format |
Article in Journal/Newspaper |
author |
Zahra Rezaei Ahmad Tahmasebi Bahman Pourabbas |
author_facet |
Zahra Rezaei Ahmad Tahmasebi Bahman Pourabbas |
author_sort |
Zahra Rezaei |
title |
Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection. |
title_short |
Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection. |
title_full |
Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection. |
title_fullStr |
Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection. |
title_full_unstemmed |
Using meta-analysis and machine learning to investigate the transcriptional response of immune cells to Leishmania infection. |
title_sort |
using meta-analysis and machine learning to investigate the transcriptional response of immune cells to leishmania infection. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2024 |
url |
https://doi.org/10.1371/journal.pntd.0011892 https://doaj.org/article/90292e6c34b44544a204cdf369c9853d |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 18, Iss 1, p e0011892 (2024) |
op_relation |
https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0011892&type=printable https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0011892 https://doaj.org/article/90292e6c34b44544a204cdf369c9853d |
op_doi |
https://doi.org/10.1371/journal.pntd.0011892 |
container_title |
PLOS Neglected Tropical Diseases |
container_volume |
18 |
container_issue |
1 |
container_start_page |
e0011892 |
_version_ |
1792045199631843328 |