Immunity | Viruses are diverse, immunity is similar

Written | Edited by Su Mu VII | Xi Although the 21st century has arrived, the outbreak of infectious diseases is still one of the major threats to the world.

In the first 20 years of the 21st century, there have been 7 outbreaks of new viral infections, including SARS-CoV-1 in 2002, H1N1 influenza in 2009, Middle East Respiratory Syndrome Coronavirus (MERS-CoV) in 2012 and 2014 Chikungunya virus (chikungunya), Ebola virus (Ebola) in 2014, Zika virus (Zika) in 2015, and SARS-CoV-2 that broke out in 2019 and is still raging to this day.
Every time you encounter a new one Viruses, we generally explore the characteristics of each virus, what kind of immune response it can cause, and what antiviral drugs can be used.

These strategies are more individualized.
For example, most of the approved antiviral drugs directly act on viral enzymes and are only effective against a few viruses, and as the virus mutates, it is very easy to develop resistance.

 So, are there similarities among so many virus infections? On March 24, 2021, the Purvesh Khatri research group of Stanford University published an article Multi-cohort analysis of host immune response identifies conserved protective and detrimental modules associated with severity across viruses in Immunity, showing that although viral infections are diverse, immune The response is similar.

Regardless of the virus, mild patients have a similar protective immune response, while in severe patients, the immune system does not work properly, and even worse results, the immune pathways involved are similar.

 The Khatri research team discovered Meta-Virus Signature (MVS) five years ago, including about 400 genes, which can distinguish viral infections, bacterial infections, and health status based on their expression levels.

However, the concern at the time was whether there was a virus infection, and there was no study on whether the symptoms of the infection were serious or not.

This time, they further studied whether the MVS gene is related to the severity of infection symptoms, from "qualitative" to "quantitative".

 The researchers collected 34 blood transcriptome data sets from 18 countries from all over the world, including 4,780 samples, ranging from infants to the elderly.

Most of them come from virus-infected people, involving as many as 16 kinds of viruses, including SARS-CoV-2, influenza virus, Chikungunya virus (Chikungunya), Ebola virus (Ebola), respiratory syncytial virus ( RSV), Rhinovirus (rhinovirus), etc.

For each sample, the researchers consulted the original literature and data, and annotated the degree of infection (see below).

 0.
Healthy people 1.
Asymptomatic infected or recovered people 2.
Mild 3.
Moderate 4.
Severe 5.
Critical 6.
Death For blood transcriptome data, the researchers used the immunoStates deconvolution method they developed The immune cell composition of each sample is broken down.

In addition, they also collected peripheral blood single-cell sequencing data integrating more than 700,000 cells from 289 samples from 170 people, most of whom were infected with COVID-19.

 It was found that regardless of the virus, the MVS score can predict the severity of the symptoms of the virus infection.
The higher the MVS score, the more severe the symptoms (the correlation is 0.
75).

This correlation can be observed in every data set as well as in new data sets.

The integrated single-cell sequencing data found that the MVS score mainly comes from myeloid cells, including CD14+ and CD16+ monocytes.

Moreover, as the severity of virus infection increases, the proportion of CD14+ monocytes increases, and the proportion of CD16+ monocytes decreases.
This is not only unique to SARS-CoV-2.
It was found through deconvolution that other viral infections also have this phenomenon.

 UMAP clustering of the samples with MVS genes found that the mildly and severely infected patients were clustered in different regions.

To this end, researchers used trajectory analysis to find genes related to the severity of symptoms, and reduced nearly 400 MVS genes to 96 key genes.

Hierarchical clustering further divides these 96 genes into four modules.
In each module, genes with large differences in expression between mild and severe cases are used as representative gene calculation module scores, and finally used for calculation and construction.
There are 42 model genes.

These four modules respectively show the similarities and differences of the immune response between severe and mild viral infections, regardless of whether they are infected with common influenza viruses or new coronaviruses.

 -Harmful Module No.
1&2: The scores of these two modules increase as the symptoms increase, and they are collectively referred to as "harmful modules".

The genes inside are mainly involved in three biological processes: increased hematopoiesis (hematopoiesis), myelopoiesis (myelopoiesis) and myeloid-derived suppressor cells (myeloid-derived suppressor cells).

To put it simply, the innate immune system is working hard to make blood, producing a large number of myeloid cells, including CD14+ monocytes and neutrophils, but to no avail, failing to control the virus, and even self-defeating and worsening symptoms.

 -Protection module No.
4 The expression of module 4 decreases with the severe increase in symptoms.
It is one of the so-called "protection modules".
The genes in it are mainly involved in two processes, one is the activity of NK and T cells, and the other is antigen presentation .

It was also observed in the single-cell sequencing data that compared with severe and mild infections, there were more NK and T cells, as well as dendritic cells responsible for antigen presentation.

In other words, to effectively fight the virus, the antigen presentation system must work normally, and the virus is presented to other immune cells, especially the adaptive immune system, which also needs to respond in a timely manner.

 -Protection module No.
3 This module is highly expressed in mild patients and is closely related to the interferon pathway.

In mild patients, these genes are in the same pace, and they are closely related to key genes in the interferon pathway, such as IFITMs, and "work together.
"
In severe cases, the expression correlation between the genes of this module is not high, and although the expression of IFITMs is also high in severe cases, the correlation between IFITMs and the genes in the module is significantly reduced, indicating that the interferon pathway and the protective module in severe cases Decoupled.

In addition, in the single-cell plasma proteome data, this module is highly correlated with the level of INFG in dendritic cells and T cells.

Using these four gene modules, the researchers defined the Severe-or-Mild (SoM) score, which can accurately distinguish severe and mild patients with different viral infections.

What is the use of studying the common immune response of the immune system to different viruses? This can speed up the development of diagnostic technology, through the immune response to predict whether a patient will be mild or severe after being infected with the virus, and optimize the allocation of medical resources, instead of having to collect data every time a new virus is encountered and start over.

In addition, identifying conservative immune responses, such as human proteins required for various viral infections, can be used to develop broad-spectrum antiviral drugs.
Buddha, the devil comes to kill the devil".

Original link: https://doi.
org/10.
1016/j.
immuni.
2021.
03.
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