Biochemical changes in lung physiology not responsible for severe clinical outcomes in the older population

In a recent study posted to the bioRxiv* pre-print server, a team of researchers investigated whether age-dependent changes in lung physiology make the elderly disproportionately susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, with an increased risk of infection severity and death compared to other age groups.

Study: Biomechanical dependence of SARS-CoV-2 infections. Image Credit: Rido/ShutterstockStudy: Biomechanical dependence of SARS-CoV-2 infections. Image Credit: Rido/Shutterstock

Global statistics on SARS-CoV-2 infection have shown that severe lung damage among older adults caused 23-fold increased mortality. Despite the statistically significantly increased disease burden in older people, it is only speculated that changes in lung physiology and weakened immunity give rise to this differential coronavirus disease 2019 (COVID-19) outcomes observed in the older population. The reasons for the age-dependent pattern of SARS-CoV-2 infection severity, which is a significant global risk factor, are unclear.

Although diseases, such as asthma, are known to increase the extracellular matrix (ECM) fiber density in the lungs of patients of any age, pulmonary fibrosis and lung stiffening make lungs more susceptible to environmental exposures and infectious pathogens, such as viruses, including SARS-CoV-2. Subsequently, lung parenchymal tissue stiffness could significantly influence SARS-CoV-2 infection and is a relevant physiological parameter that might partially explain age-dependent differences in infection severity.

About the study

In the current study, researchers focused primarily on the biomechanical changes in lungs, including lung parenchymal stiffening and augmented matrix fiber density, of the elderly and young and quantified their impact on the susceptibility of SARS-CoV-2 infection.

The researchers examined changes in infection rates and studied SARS-CoV-2 infection dynamics with parenchymal tissue stiffness of lung epithelial cells. To this end, they cultured Calu-3 airway epithelial cells on hydrogels with elastic moduli of 0.2 and 50 kPa and used conventional tissue culture surfaces. Additionally, they used sparse or dense electrospun polycaprolactone (PCL) fiber matrices, mimicking ECM densification.


During the experiments, the D614G PV was almost 10-fold more potent than the wild type (WT) PV on both hydrogel substrates, but not rigid tissue culture polystyrene surface (TCPS). This observation suggested that the variant’s tuning compliance with the substrate drastically impact its infection potential.

Increased ECM fiber density of stiffer (older) lungs facilitates the sticking of pathogens, thus increasing the infection probability. Since the hydrogel system does not de-couple stiffness from fiber density, the authors used PCL fiber matrices to mimic the geometrical properties of ECM fibers. 

The authors noted an average of 2.5 times more fibers on the dense scaffolds, while cells formed smaller cell clusters. Cells on sparse fibers showed more infection events for the WT and D614G variants. Interestingly, the D614G variant lost its increased efficiency relative to the WT on both sparse and dense electrospun mats, suggesting nanofiber scaffolds on glass have unique features.

SARS-CoV-2 PVs infection in Calu-3 cells was stiffness-dependent, indicating that angiotensin-converting enzyme 2 (ACE-2) expression is modulated by cell-material interaction. Although both HEK 293T cells and Calu-3 cells expressed ACE-2 in clusters, clustering was more prominent in the Calu-3 cells.  

When authors compared the ACE-2 expression on the hydrogel substrates, they noted a significant decrease in ACE-2 expression with increasing stiffness. Additionally, Calu3 cells expressed more ACE-2 on dense scaffolds than sparse fibers, opposed to cell cluster size, thus suggesting that cells on softer substrates showed more PV infection.

Calu-3 lung cells grown on softer surfaces and incubated with PVs showed increased infection compared to stiffer hydrogels and TCPS by 4.8-fold and 1.6-fold, respectively. A possible mechanism underlying this mechanosensitivity of viral infection is that cells can sense the local mechanical environment and respond by changing their mechanics or expression profiles.

Previous studies have shown that SARS-CoV-2 interacts with different macrophages, where the phenotype with the most cell membrane stiffness showed the lowest viral uptake. Additionally, ECM substrate stiffness affects cell phenotype via an epithelial-to-mesenchymal transition to modify viral uptake. Since Calu-3 does not transition to a mesenchymal phenotype, even under TGF-β1 stimulation, the authors did not observe similar phenomenons in the current work.

The results also showed that SARS-CoV-2 infection was more dependent on ACE-2 expression for the hydrogels, with cells on the 0.2kPa substrate expressing more ACE-2 and exhibiting higher initial infection than on the 50kPa substrate. Contrastingly, on the fiber matrices, the cell surface area appeared to become a more important factor, which might explain why the D614G variant loses its potency.


Although the study provided experimental evidence that softer lung tissues of older adults facilitate SARS-CoV-2 infection, especially by D614G variant and sufficient ACE-2 expression; the findings also indicated that severe clinical outcomes in older COVID-19 patients were not necessarily due to biomechanical changes in lung tissue parenchyma.

The findings raised the possibility that the ECM microenvironment and tissue stiffness could modulate the post-infection replication of SARS-CoV-2 and subsequent immune response. Therefore, the authors recommended that future studies should explore these aspects.

*Important notice

bioRxiv publishes preliminary scientific reports that are not peer-reviewed and, therefore, should not be regarded as conclusive, guide clinical practice/health-related behavior, or treated as established information.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.


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