Global proteomics reveals pathways of mesenchymal stem cells altered by Mycobacterium tuberculosis.

doi:10.21203/rs.3.rs-4179764/v1

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Global proteomics reveals pathways of mesenchymal stem cells altered by Mycobacterium tuberculosis.

https://doi.org/10.21203/rs.3.rs-4179764/v1

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Mycobacterium tuberculosis (M. tb) has a remarkable ability to persist inside host cells. Several studies showed that M. tb infects and survives inside bone marrow mesenchymal stem cells (BM-MSCs) escaping the host immune system. Here, we have identified various cellular pathways that are modulated in human BM-MSCs upon infection with virulent M. tb and the proteomic profile of these cells varies from that of avirulent M. tb infected cells. We found that virulent M. tb infection reshapes host pathways such as stem cell differentiation, alternative splicing, cytokine production, mitochondrial function etc., which might be modulated by M. tb to persist inside this unconventional niche of human BM-MSCs. Additionally, we observed that virulent M. tb infection suppresses various cellular processes. This study uncovers the differences in the host proteomic profiles resulting from the virulent versus avirulent M. tb infection that can pave the way to identify host-directed therapeutic targets for the treatment of tuberculosis.

Biological sciences/Biochemistry/Proteomics

Health sciences/Diseases/Infectious diseases/Tuberculosis

Biological sciences/Microbiology/Bacteria/Bacterial host response

Host-directed therapeutics

Mesenchymal stem cells

Mycobacterium tuberculosis

Proteomics

Pathway analysis

In spite of the tremendous efforts, control of tuberculosis (TB) still remains a challenging task. Moreover, the onset of COVID-19 pandemic in 2020 has negatively impacted the progress made towards TB elimination in the past few years. According to WHO, in 2021, an estimated 10.6 million people fell ill with TB globally, out of which 1.6 million people died due to the disease (1). Apart from this, one-fourth of the world’s population is infected with dormant M. tb, which is at a lifetime risk of reactivation into active disease (1). M. tb displays a remarkable tendency to modulate its active metabolic state to dormant state in the host and hides in various unconventional niches evading host immune surveillance, stressful environment as well as antibiotic treatment (2). Therefore, in order to target these dormant bacteria, there is a need to understand the mechanisms of survival and persistence of dormant M. tb in such unconventional niches. One such niche is bone marrow mesenchymal stem cells (BM-MSCs), wherein bacteria can persist without getting eliminated by anti-TB drugs posing a threat for reactivation (3-10). Our laboratory has previously demonstrated that M. tb when residing inside BM-MSCs was unresponsive to the action of anti-TB drugs as compared to when residing inside THP-1 macrophages, owing to the upregulation of host ABCG2 efflux pumps resulting in an enhanced efflux of the anti-TB drugs (11). Since, M. tb and other pathogenic organisms are known to hijack host machinery and modulate the host cellular pathways for their own survival advantage, a detailed understanding of such mechanisms/pathways altered in hBM-MSCs by M. tb infection would help us to design novel strategies to target M. tb residing inside hBM-MSCs and eliminate this pathogen reservoir. Several studies have been conducted in macrophages where proteomics-based approach was employed for comprehensive study of the host proteome. Menon et al. have employed quantitative proteomics to understand the importance of lipid metabolism and host defence mechanisms in tackling bacterial infection (12). Another study has showed that the exposure of mycobacterial cell wall lipids induces differential expression of several proteins in macrophages belonging to immune response, vesicle transport, oxidation and reduction and many more cellular processes (13). These studies highlight the importance of proteomics-based strategies for the identification of various novel proteins and pathways that help in better understanding of host-pathogen interactions.

In this study, we focused on identification of the changes induced by pathogenic M. tb in the proteome of human BM-MSCs to favour its own survival and further protect the pathogen from antibiotic assault and immune response by using global label-free proteomics approach. For this, to identify various proteins and pathways of hBM-MSCs that are modulated specifically with virulent M. tb infection, proteomics study was conducted with hBM-MSCs infected with the virulent as well as the avirulent M. tb strains. It is known that both M. tb H37Rv (virulent) and M. tb H37Ra (avirulent) are closely related strains of mycobacteria which differ mainly in their virulence potential (14). Despite having equivalent MIC values for anti-TB drugs, these strains differ at their genetic and protein levels (15). M. tb H37Ra bears a mutation in the phoP gene that encodes for a response regulator of the PhoP/PhoR two-component system. PhoP is essential for the virulence and is known to regulate several downstream genes including ESX-1 secretion system (16). In the absence of ESX-1 secretion system, the pathogen is unable to release mycobacterial effector proteins into the host which might contribute to its avirulent nature. Moreover, it has been shown that M. tb H37Ra infects lungs and other organs with lower bacterial loads as compared to M. tb H37Rv, which fails to cause disease (17). Apart from this, it has been previously demonstrated that infection with virulent or avirulent strain of M. tb invokes different expression profile in macrophages, suggesting the existence of different immunity mechanisms (18). Uncovering the pathways that work differently in the virulent and avirulent infection highlights their importance in the host defence. and thus makes them potential targets for host-directed therapeutic approach for the elimination of the pathogen from the host.

Propagation of hBM-MSCs

The hBM-MSCs were procured commercially and were successfully cultured and propagated. The cells achieved a confluency of ~80-90% in 6-7 days of revival and it was observed that passaging of the cells at less than 60-70% confluency resulted in extremely slow proliferation of the cells, thereby, suggesting the importance of cell-cell contact during expansion of hBM-MSCs in ex vivo culture. Figure 1 shows the images of the cells during propagation, wherein, long spindle-shaped and flattened cells were observed in the culture dishes, which is a characteristic morphological feature of the mesenchymal stem cells. Fig 1A represents cells observed at 3-4 days post culturing, whereas Fig 1B, represents cells observed after 6-7 days post culturing. It was noted that the cells grew in a healthy manner till passage 2, however, subsequently their growth rate was decreased. Hence, passage 2 cells were employed for all the studies.

Confocal microscopy of hBM-MSCs infected with M. tb

To verify the infection of cultured hBM-MSCs with M. tb, we performed confocal microscopy to visualize GFP expressing M. tb in hBM-MSCs after infection. Briefly, the cells were infected with M. tb H37Rv-GFP strain by employing the protocol described in the 'materials and methods' section. The cells were fixed post infection and were stained with PKH26 dye and DAPI to label the cell membrane and the nucleus of the cells, respectively. It was observed that the bacteria were intracellularly localised inside hBM-MSCs as observed by GFP fluorescence in the cells (Figure 1C and 1D). Thus, this confirmed the localisation of the M. tb inside hBM-MSCs and provided a validation for the infection protocol.

Virulent M. tb persists inside hBM-MSCs

In order to perform a global proteomics study of hBM-MSCs infected with M. tb, it was required that the sample for proteomics analysis comprised of a high number of M. tb infected viable cells. In other similar ex-vivo studies involving M. tb infection, varying multiplicity of infections (MOIs) in the range of 1:10 to 1:50 have been employed (8, 17-18). Hence, we evaluated the percent infection of hBM-MSCs at two high MOIs i.e, 1:30 and 1:50. We observed that an infection with MOI 1:50 resulted in greater than 60% of infection without any significant loss of cellular viability, while an MOI of 1:30 led to ~49% infection (Figure 1E and 1F). Hence, the MOI of 1:50 for M. tb infection of hBM-MSCs for conducting proteomic study was selected.MSCs have been shown earlier to provide a protective niche to M. tb. It was shown that M. tb possesses the ability to survive and persist inside BM-MSCs by evading the immune surveillance and antibiotic treatment, however, the mechanisms responsible for the same are poorly understood. Therefore, we performed an untargeted global LC-MS/MS based proteomics which would reflect the dynamic state of the cellular proteome and will provide accurate overall protein signatures of a genome. Identifying various host proteins/pathways that are altered in hBM-MSCs by M. tb infection would help in bridging the gaps in the understanding of the mechanism(s) of pathogen’s survival inside hBM-MSCs. Moreover, along with the virulent M. tb strain, we have also employed the avirulent M. tb H37Ra strain to specifically identify the proteins/pathways modulated inside hBM-MSCs upon infection with virulent M. tb. Towards this, a growth kinetic study was carried out for both the strains of M. tb i.e., virulent M. tb H37Rv and aviruent M. tb H37Ra, in order to determine the growth rates of these strains inside hBM-MSCs. It was observed that the virulent M. tb H37Rv strain was able to replicate inside hBM-MSCs till day 4 and thereafter, bacteria remained viable in a non-replicative manner albeit constantly maintaining the bacterial CFU. This observation corroborated with the earlier observation of M. tb reaching a dormant state in hBM-MSCs (3, 10). However, the avirulent M. tb H37Ra strain, replicated initially till day 4 inside hBM-MSCs with a subsequent decline in the bacterial CFU from day 6 onwards. At day 10, the avirulent strain exhibited ~0.5 log reduced CFU as compared to the virulent strain (Figure 1G). Thus, the virulent M. tb is able to adapt more efficiently and remains dormant and in non-replicating state inside hBM-MSCs as compared to the avirulent M. tb, wherein, the host is able to combat the infection as observed by a decline in the CFU of avirulent M. tb. This differential ability of the host can be understood by global proteome profiling of virulent versus avirulent M. tb infected hBM-MSCs to delineate the mechanisms hijacked specifically by virulent M. tb for its own advantage and survival.

M. tb infection drives global cellular proteomic remodelling in hBM-MSCs

Figure 2A shows the design of the experimental protocol followed to conduct the proteomics study. We detected 2476 proteins in H37Rv infected hBM-MSCs lysate; whereas 2519 proteins were identified in H37Ra infected hBM-MSC lysate and a total of 2503 proteins were detected in uninfected control sample. This represented ~12.5% of the total human proteins that were detected in our investigation. Before further analysis, various statistical models were employed (2D-PCA and correlation matrix) in the study to determine the uniformity, robustness and reproducibility of the protein abundance levels obtained after MS (Figure 2B-2D) (19-21). Downstream analysis of expressed proteome using amica showed significant reproducibility among the independent replicates. We observed varied global profiles in the protein data sets across different groups (M. tb H37Rv-infected, M. tb H37Ra-infected and uninfected hBM-MSCs with less variation among the three independent replicates of a particular group (Figure 2B and 2C). This suggested that the independent replicates were highly reproducible and the overall proteome of the hBM-MSCs altered significantly after infection as compared to uninfected state. As expected, we also observed that the virulent and avirulent strains of the bacteria evoke different protein expression outcomes in the host.

After establishing the reproducibility between the replicates, the proteomes of M. tb H37Rv-infected and M. tb H37Ra-infected hBM-MSCs were thoroughly analysed to determine the differentially expressed proteins (DEPs) induced as a result of bacterial infection. For this, three analysis groups were employed, namely, M. tb H37Rv-infected hBM-MSCs versus uninfected hBM-MSCs control (Rv Vs UI), M. tb H37Ra-infected hBM-MSCs versus uninfected hBM-MSCs control (Ra Vs UI) and M. tb H37Rv-infected hBM-MSCs versus M. tb H37Ra-infected hBM-MSCs (Rv Vs Ra) (Supplementary information S1). Critical evaluation of the differentially expressed proteins (DEPs) (>log2FC, pValue <0.05) by visualizing the volcano plots and unsupervised hierarchical clusters showed notable and reproducible pattern of enriched and depleted proteins (Figure 3). Volcano plots and Heat map analysis for comparison of the relative protein expression profiles amongst the three analysis groups reflected that the levels of majority of the host proteins altered upon virulent M. tb H37Rv infection in hBM-MSCs had decreased expression in comparison to the DEPs of hBM-MSCs infected with avirulent M. tb H37Ra strain (Figure 3A-3F, Table 1). In the venn diagram-based distribution analysis of DEPs upon infection with M. tb H37Rv in comparison to uninfected and intra-infection (M. tb H37Ra), proteome profile again revealed that the virulent infection resultant changes were more towards translational inhibition (downregulation of proteome) rather than increased synthesis (upregulation of proteome) (Figure 3G, 3H). Comparison of DEPs of M. tb H37Rv infected versus M. tb H37Ra infected hBM-MSCs led to the identification of 141 distinct host proteins whose expression levels were altered exclusively by virulent M. tb infection. Out of these, the expression levels of 33 proteins were increased and the levels of 108 proteins were decreased significantly in the hBM-MSCs. Thus, these results clearly indicate that the virulent M. tb infection reshapes the host machinery and cellular pathways majorly by suppressing the levels of several proteins to survive inside the host hBM-MSCs. We also observed that 46.5% of the repressed proteins were representative of the virulent M. tb H37Rv infection as compared to the avirulent M. tb H37Ra infection while 66% of the proteins whose expression was induced upon infection were from the avirulent M. tb infection as compared to the infection with the virulent strain (Figure 3G, 3H). Moreover, it was observed that there is strain specific dysregulation of protein expression that suggests integration of mRNA and miRNA expression levels with protein levels that can be investigated further.

Gene Ontology (GO) and pathway analysis-insights into specific cellular changes in host upon infection

To elucidate the functional and biological relevance of the bacterial infection derived DEPs of hBM-MSCs, all the DEPs were subjected to identification of key gene ontology (GO) and pathways that were enriched harboring the DEPs in a statistically significant manner (Supplementary information S2). Clustering of enriched GO and pathways was performed and visualized as Balloon plot. A total of 19 GO and pathways were identified such as amino acid biosynthesis, calcium signaling, cell adhesion, cell adhesion and migration, collagen, extracellular matrix (ECM), host-pathogen interaction, immune response, lipoproteins, mitochondrial electron transport function, mitochondrial function, ROS response, proteases, protein ubiquitination, protein folding, vesicle trafficking, secretory protein transport, translation, and splicing (Figure 4A, 4B). Moreover, it was observed that most of the altered proteins whether it showed increased or decreased expression in any of the infected groups, belonged to the pathways related to host-pathogen interactions, collagen/cell adhesion, immune response, mitochondrial function, lipoproteins, splicing/translation, and vesicle trafficking (Figure 4 A, 4B). On further analysis, we observed that in the case of avirulent M. tb H37Ra infected hBM-MSCs versus uninfected hBM-MSCs, proteins belonging to pathways such as ROS response, ubiquitin proteolysis pathway, mitochondrial electron transport function (bioenergetics) and lipoproteins were found to be enriched, whereas proteins of these pathways were either unchanged or exhibited decreased expression in the M. tb H37Rv infected cells versus uninfected cells (Figure 4 A, 4B). The enrichment of these specific pathway proteins in host hBM-MSCs infected with avirulent M. tb suggests their involvement in the host mechanisms to kill M. tb H37Ra, whereas, the decreased expression of these proteins in the virulent M. tb infected hBM-MSCs, further substantiates that these proteins are required by the host cells to combat infection and virulent M. tb suppresses them for its own survival advantage. In the case of analysis group virulent M. tb H37Rv infected hBM-MSCs versus uninfected, it was observed that proteins belonging to pathways related to vesicle trafficking, cell adhesion and migration, collagen, host-pathogen interactions, proteases, protein transport, and mitochondrial function were depleted, which were mostly unchanged in avirulent M. tb infected host cells, again pointing out to the fact that the virulent M. tb infection suppressed various pathways. This was interesting to note that there was an overall shutdown/suppression of the various key pathways by virulent M. tb infection that might be one of the strategies of this smart pathogen for its survival in the host cells and cause rewiring of these host immune-protective mechanisms for its own advantage. These enriched GO and pathways were considered as bridges and DEPs were considered as the nodes that connect the bridges. All the DEPs along with their biological role (GO and pathways) that was provided as input to RegNet algorithm (Theomics international Pvt. Ltd.) resulted in the modeling of protein:protein, protein:pathway, and protein:ontology along with the fold change and p-value (Student’s t-test) for each of the DEP. The nodes were coloured according to their log₂ ratios (abundance ratio) for each group. The bridge file output of the algorithm was visualized using Cytoscape v 2.8.3 to resolve the core protein network encompassing the DEPs like IL1B, COL1A1, CTGF, COL1A2, COL3A1, CXCL8, COL5A1, MMP14, MMP13, THBS2, COL12A1, CXCL1, LAMB1, APOE etc., that regulates host-pathogen interaction, immune response, collagen, ECM, cell adhesion and migration, and mitochondrial function (Figure 4C-E).

The DEPs of pathways such as collagen, ECM, cell adhesion, proteases were strongly clustered and inter-related while host-pathogen interaction and immunity related DEPs formed another strong cluster. Most of the proteins found in ‘Rv Vs UI’ were altered as against their basal levels in uninfected cells suggesting that the proteome profile of hBM-MSCs was severely modulated by M. tb infection (Figure 4C) while the same proteins were mostly unchanged in case of infection with avirulent M. tb H37Ra infection (Figure 4D). Moreover, in the most critical network analysis group (Rv Vs Ra), the repressed protein nodes were of utmost importance because these proteins were suppressed in the host cells due to M. tb H37Rv infection, but were either unchanged or enriched in M. tb H37Ra infected hBM-MSCs (Figure 4E). Therefore, they might represent the specific protein players involved in bacterial killing mechanism by the host. The pathways altered upon infection with virulent M. tb strain were further categorized into seven categories namely, RNA binding/alternate splicing, autophagy/vesicle fusion, ubiquinone synthesis/mitochondrial bioenergetics, metalloproteases, phagosome-endosome fusion, immune response related, and collagen/ECM/cell adhesion (Figure 4F). Supplementary information S1 lists the DEPs associated with these pathways.

Thus, the proteins regulating these pathways offer a chance for further investigation to target virulent bacteria residing inside the hBM-MSCs.

Expression analysis for genes encoding DEPs

To experimentally validate the proteomics results, we performed real time PCR analysis for a few genes encoding the DEPs namely, cxcl-10, mmp13, col1a2, clecb3, grem-1, uqcrh, gpx-1, and hnrnpk. For this, the total RNA was isolated from hBM-MSCs infected with virulent /avirulent M. tb strains/uninfected cells and was converted into cDNA by using the protocol mentioned in the ‘materials and methods’ section. Real time PCR was conducted for each sample by employing gene specific primers (Table 2) and ΔCt values were calculated after normalising the Ct values with gapdh (Figure 4G). It was found that the mRNA levels of cxcl-10, clecb3 and grem-1 were significantly upregulated and the expression levels of uqcrh, gpx-1 and hnrnpk were downregulated in virulent M. tb infected hBM-MSCs as compared to avirulent M. tb infected and uninfected cells. Additionally, no significant difference was observed for the expression levels of mmp13 and col1a2 between the hBM-MSCs infected with M. tb H37Rv and H37Ra strains, however, on comparing M. tb H37Rv infected hBM-MSCs with uninfected cells, the expression levels of mmp13 and col1a2 was increased and decreased, respectively, suggesting a global alteration of these genes in the host cell in response to infection. The alterations observed in the levels of mRNA were consistent with the protein abundance levels of these genes products in the proteomics results. Hence, these results substantiated our observations that infection with M. tb indeed alters the relative protein quantities in hBM-MSCs.

Mycobacterium tuberculosis causes tuberculosis in humans and is one of the most successful pathogens. Its success lies in its ability to withstand the host mounted defences and to also undergo physiological adaptations by switching its metabolic state from active to latent state and vice-versa. Regardless of the presence of effective anti-TB drugs and a vaccine, M. tb continues to remain a global menace. Therefore, to fight the battle against this pathogen, designing of novel improved interventions is imperative.

BM-MSCs have been found as a niche for dormant M. tb (3). However, the mechanism(s) by which the pathogen survives and persists inside these mesenchymal stem cells is poorly understood. Hence, knowledge of the key regulatory pathways/proteins of the host that are hijacked by M. tb post infection for its own persistence would be extremely useful in formulating novel approaches to kill these hidden bacteria and eliminate TB. Thus, in this study, changes in the proteomics profile of hBM-MSCs as a result of infection with virulent M. tb H37Rv/avirulent H37Ra strains was investigated by using a high throughput tandem MS-based proteomics approach. We demonstrated that unlike the virulent M. tb, avirulent strain of the bacteria is susceptible to host-mediated killing pathways and therefore, their viability starts to decline inside hBM-MSCs, however, the former strain continues to persist. This observation was in agreement with other studies, where the authors have demonstrated that the attenuated strain of M. tb gets killed by the action of cathelicidin inside BM-MSCs, whereas M. tb H37Rv could resist and therefore, was able to survive and persist inside these cells (7).

Further, we conducted a label-free MS-based proteomic analysis of M. tb H37Rv-infected, M. tb H37Ra-infected and uninfected hBM-MSCs, separately, where M. tb H37Ra-infected hBM-MSCs and uninfected cells were considered as reference controls for identifying M. tb H37Rv induced specific alterations in hBM-MSCs at the proteome level. It was found that the data generated by LC-MS/MS was reproducible (as assessed by 2D- PCA plot and correlation matrix) across all the three biological replicates of the 3 groups.

Various DEPs of hBM-MSCs were identified whose expression levels were altered upon M. tb infection as compared to uninfected control. Further, comparison of DEPs of M. tb H37Rv infected versus M. tb H37Ra infected hBM-MSCs led to the identification of 141 distinct host proteins whose expression levels were altered exclusively by virulent M. tb infection. Out of these, the expression levels of 33 proteins were increased and the levels of 108 proteins were decreased significantly in the hBM-MSCs. Enrichment analysis of GO and pathways harbouring differential proteome revealed that M. tb H37Rv infection when compared to M. tb H37Ra infection causes modulation of host proteins involved in major cellular processes such as RNA binding and splicing, immune response, mitochondrial function, vesicle trafficking, collagen related, ECM/cell adhesion etc. A very large complex network between DEPs was observed suggesting functional inter-connections between various pathways emphasizing on the overall reprogramming of several processes of hBM-MSCs by virulent M. tb for its survival and persistence.

Several studies have also demonstrated similar reprogramming and modulations of pathways in macrophage cells (primary host niche) after infection with M. tb. Various mechanistic strategies adopted by the pathogen have also been elucidated based on these studies conducted in infected macrophages such as, downregulation of autophagy, changes in cytoskeleton for pathogen’s movement and dissemination in the host cell and alteration in the cytokine profie of macrophage resulting in reduced innate immune response (22-24).

Our study shows that M. tb can manipulate and modulate hBM-MSCs and some of the key pathways and proteins involved in the process are described below. It has been observed that the factors such as, EIF5B, EIF4G2, RPS27, RPS3, SRSF2, SRRM2, HNRNPK, and RNPS1 involved in RNA binding, translation, and splicing process showed significant depletion exclusively upon virulent M. tb infection. EIF4G2 and EIF5B are eukaryotic translation initiation factors that are known to dictate synthesis of proteins involved in various crucial processes (25). A study showed that low-level of EIF5B is responsible for suppressed cell growth and proliferation and alters the cellular pathways associated with stress responses (26). Similarly, EIF4G2 silencing also led to cellular growth inhibition, suppression of metastasis and tumorigenesis by inhibiting ERK signalling pathway in the case of hepatocellular carcinomas (27), signifying the importance of initiation factors in the cell proliferation. We also observed reduced levels of RNA binding factor RPS27, which is known to be associated with several biological processes such as proliferation, apoptosis, protein synthesis, alternate splicing (28-29). Various investigators have shown the involvement of RPS27 in mediating innate immunity by activation of NF-kB signaling pathway (28-29). RPS3, another ribosomal protein, that is induced by oxidative stress and bacterial infection has been shown to be involved in NF-kB mediated transcription of pro-inflammatory cytokines (30-31). Hence, modulation in the expression levels of these proteins suggests that virulent M. tb targets ribosomal proteins to inhibit the host immune defence mechanisms, which is well suited for its survival in this niche. Alternative splicing is another crucial process that has been shown to be altered by various pathogens (32). Infection of macrophages with virulent M. tb has been shown to affect alternate splicing resulting in various spliced or truncated versions of various genes (33). We observed a decline in the levels of splicing proteins SRSF2 and SRRM2. The gene encoding for SRSF2 was also found to be downregulated in THP-1 macrophages after M. tb infection (34). Penn et al. demonstrated physical interaction of splicing proteins including SRSF2 and SRRM2 with M. tb secreted protein Rv1827, highlighting a crucial role of host-pathogen interactions resulting in dynamic reprogramming of the host transcriptome (35).

We also observed that several proteins involved in mitochondrial function and bioenergetics (UQCRH, NDUFA8, SLC25A11, SLC25A4, OXCT-1, GPX-1) were significantly decreased in virulent M. tb infected hBM-MSCs. In the case of macrophages infected with M. tb, a metabolic shift in the host energy metabolism is observed that is directly related to the cellular immune responses against the pathogen invasion (36-37). However, for stem cells, a reduction in oxidative phosphorylation and mitochondrial respiration has been linked with maintenance of their stemness properties and reduced differentiation abilities (38-39). Thus, we believe that hBM-MSCs after virulent M. tb infection switch over to quiescence as a result of host mitochondrial reprogramming and decreased oxidative phosphorylation and ATP production. This appears to be useful for M. tb survival and evasion to keep this host cell niche in an uncommitted quiescent state. However, further investigations will be required to validate this.

In addition to this, we observed that proteins belonging to ECM and collagen family (COL3A1, COL1A2, COL5A1, GREM-1, FBLN-1, THBS2, NID2) were highly altered upon M. tb infection. Previous studies have shown that during host infection, M. tb secretes factors that induce various host matrix metalloproteases to degrade ECM and collagen proteins and thereby, ensures their invasion and establishment of infection inside the cells (40-41). Moreover, it has been known that in mesenchymal stem cells, collagen and ECM proteins regulate their differentiation and proliferation properties (42-44). In our study, we observed that various collagen proteins like COL3A1, COL1A2 were significantly reduced, whereas COL5A1 was enriched. These proteins are known to have a direct role in the differentiation of MSCs, as higher levels of COL3A1 and COL1A2 promote osteogenic differentiation of MSCs (45-46), whereas higher levels of COL5A1 inhibits osteogenic differentiation capacity of the multipotent stem cells (47). Similarly, we observed high expression of GREM-1 (Gremlin-1) which is an antagonist of BMP (bone morphogenetic protein, involved in osteogenic differentiation of stem cells) (48). GREM-1 has been demonstrated to inhibit osteogenic differentiation and senescence in stem cells (49). Apart from this, we observed increase levels of thrombospondin (THBS2), which is known to inhibit osteogenic differentiation and MSCs proliferation (50-52). Moreover, the levels of proteins such as filbulin-1 (FBLN-1) and nidogen-2 (NID2), that induces osteogenic differentiation, were also found to be reduced in our study (53-55). Hence, specific alterations in these proteins involved in differentiation of stem cells indicate that the pathogen restricts the stem cells from differentiation, keeping them in an undifferentiated state that may be required for its own benefit to survive longer in the niche. However, a further detailed investigation into this phenomenon of M. tb survival will be required.

We also observed alterations in the proteins belonging to vesicular trafficking and protein transport. It has been previously demonstrated that autophagy can be an intrinsic mechanism for fusion of mycobacterial phagosome to lysosomes to kill intracellular M. tb (6). Hence, reducing the autophagy and vesicular trafficking pathways could be a strategy for M. tb to persist in MSCs. Along the same lines, we observed a significant reduction in the expression of RAB5B and RAB5C, which are known regulatory GTPases and function in endocytic pathway of phagocytic cells (56-57). Moreover, various dynein motor proteins involved in vesicle transport (DYNC1I2, DYNLL1) were also found to be decreased in hBM-MSCs upon M. tb infection. These proteins have been earlier shown to be involved in directing phagosomes towards lysosomes, and thus, are involved in promoting phagosome-lysosome fusion and pathogen killing (58). Moreover, various proteins of vacuolar protein sorting complexes were found to be modulated by M. tb inside hBM-MSCs, such as VPS26A, VPS45, and VPS36. These are known to be involved in autophagy, cargo binding and selectivity and trafficking of vacuolar cargo (59-62). Hence, downregulation of these proteins suggests that M. tb subverts the vesicular trafficking, autophagic response and protein transport for its survival.

Additionally, our data showed that proteins involved in immune responses such as CXCL-1, CXCL-6, CXCL-8 and CXCL-10, were increased upon M. tb infection in hBM-MSCs which is in accordance with the vital role of these pro-inflammatory cytokines in fighting against invading pathogens and attracting various immune cells like neutrophils, monocytes, T cells and B cells at the site of injury/inflammation (63). Therefore, upregulation of these cytokines involved in innate immune response can be directly correlated to the hBM-MSCs response towards bacterial antigens. (64-67).

Taken together, our analysis revealed that M. tb modifies the host cellular dynamics extensively by altering key regulatory proteins and hijacking major functional pathways for its persistence and survival inside hBM-MSCs. Based on these results, we speculate that M. tb attempts to drive hBM-MSCs towards a state of quiescence by maintaining stemness of the cells, reducing cell differentiation and proliferation pathways; suppressing proteins involved in splicing and translation; and decreasing the intracellular vesicular trafficking and autophagy (Figure 5). We believe that by modulating these host pathways, M. tb creates an inert environment for itself to thrive and perpetuate inside unconventional niche of hBM-MSCs. However, further investigations are needed to confirm these proposed strategies/mechanisms. This is the first study to report the proteomics profile of M. tb infected hBM-MSCs that compares changes in the abundance levels of proteins induced by virulent versus avirulent M. tb infection inside hBM-MSCs. Thus, this study has led to an increased understanding of the changes induced by pathogenic M. tb in the proteome of hBM-MSCs to favour its own survival, which paves the way for design and development of new host-directed therapeutic targets to kill this dormant population of M. tb from the host niches and prevent the problem of TB reactivation.

Bacterial culture and growth conditions

M. tb strains (virulent M. tb H37Rv and avirulent M. tb H37Ra) were grown in Middlebrook 7H9 broth medium (Becton Dickinson) supplemented with ADC (Albumin- Dextrose-Catalase) (Becton Dickinson), 0.5% glycerol and 0.2% Tween 80 with constant shaking at 200 rpm, 37°C. Recombinant M. tb GFP strain was grown in the same conditions in the presence of 25µg/ml kanamycin.

Culturing of cells

Human bone marrow mesenchymal stem cells (hBM-MSCs) were procured commercially from Thermo Fisher Scientific (catalog number-A15652) and were propagated in MesenPRO RS^TM basal medium supplemented with MesenPRO RS^TMgrowth supplement (Gibco, catalog number- 12746012). Briefly, the cells were revived by thawing a stock vial at 37°C in a humidified 5% CO₂ incubator followed by addition of 1 ml supplemented media to the vial. The contents were transferred to a T-25 flask and incubated at 37°C in a humidified 5% CO₂ incubator. After 24 hours, the culture medium was replaced with fresh media and the cells were cultured for ~6-7 days till they reached a confluency of 70-80%. Further, the cells were split (ratio 1:2) in two T-25 flasks after trypsinization with 0.025% trypsin (CTS^TM trypLE^TM select enzyme, Thermo Fisher Scientific). The cells were propagated till passage 2 and then employed for conducting all the experiments.

Infection of hBM-MSCs with M. tb

The hBM-MSCs were infected with M. tb H37Rv-GFP expressing strain for confocal microscopy studies. hBM-MSCs were seeded on circular coverslips washed with 70% Ethanol and dulbecco’s phosphate buffer saline (DPBS) and were incubated at 37°C, 5% CO₂ for 16 hours. A logarithmic phase culture of M. tb H37Rv-GFP cells was harvested, washed with 7H9 media, and employed for single cell preparation by using a previously published protocol (68). Subsequently, the hBM-MSCs were infected with M. tb H37Rv-GFP bacteria at an multiplicity of infection (MOI) of 1:10 (hBM-MSCs: bacteria) for 8 hours followed by amikacin (200 μg/ml) treatment for 1 hour to remove the extracellular bacteria. The cells membrane were then stained with 2 μM PKH26 dye (Merck) for 15 mins at room temperature (RT). The cells were then fixed with 4% paraformaldehyde (PFA) for 1 hour followed by mounting of the coverslips onto the glass slides by using DAPI (4',6-diamidino-2-phenylindole) antifade stain (Invitrogen) followed by sealing of the coverslips. The cells were visualized by using Leica TCS SP8 confocal laser scanning microscope (Leica Microsystems).

Growth kinetics of M. tb inside hBM-MSCs

hBM-MSCs were infected with M. tb H37Rv (virulent) and M. tb H37Ra (avirulent) strains, separately at an MOI of 1:5 by using the protocol as mentioned above and incubated at 37°C in 5% CO₂. The bacterial burden inside the cells was evaluated by CFU enumeration at various time points (day 0, 2, 4, 6, and 10). For this, the cells were lysed by the addition of 0.025% sodium dodecyl sulfate (SDS) solution for 15 mins at 37°C and the lysate was subjected to centrifugation at 12,000 rpm for 10 mins at 4°C. The supernatant was discarded and the pellet was resuspended in 100 µl 7H9 medium. Appropriate dilutions of the samples were plated onto 7H11 agar plates and the plates were incubated at 37°C for 3-4 weeks.

Quantification of M. tb infection by using flow cytometry

The optimum MOI with highest percentage of infected cells was determined for conducting the proteomics study. Briefly, the hBM-MSCs were grown till passage 2 and seeded in a 6-well plate for overnight at a density of 2x10⁵ cells/well. The cells were infected with M. tb H37Rv-GFP at different MOIs of 1:30 and 1:50 (hBM-MSCs: bacteria) by employing the protocol as mentioned above. After infection, the cells were retrieved, fixed by using 4% PFA solution for 30 mins, and washed with DPBS for further evaluation by FACS for percent infection. The uninfected cells were employed to set voltages for forward scattering (FSC) and side scattering (SSC) in the plot. The infected cells were run at fluorescein iosothiocyanate (FITC) channel to obtain the values of percent infection. The cell viability was also checked by flow cytometer by using 7AAD staining which is a fluorescent marker for determining the cellular viability. For this, the cells were immediately mixed with 2µl of the staining solution before acquisition in the flow cytometer. The cell counts were also determined by trypan blue staining.

Label free mass spectrometry based proteomics

The hBM-MSCs were seeded in a 6 well flat bottom plate at a density of 1X 10⁶cells per well in triplicates (independent triplicates from 3 different passages of cells) and were infected with M. tb H37Rv and M. tb H37Ra cells, separately at an MOI of 1:50 (hBM-MSC: bacteria) for 48 hours at 37°C in a humidified 5% CO₂ atmosphere. After 48 hours of infection, culture medium was aspirated from each well. Uninfected hBM-MSCs were employed as control. All wells were washed with 1 ml DPBS to remove any residual media components. The adherent cells were scraped and resuspended in G-buffer [0.1M tris (pH 8.5) and 6M guanidine hydrochloride] preheated at 70°C, supplemented with 1X protease inhibitor cocktail (Roche). The lysed cell mixture was subjected to centrifugation at 14,000 rpm for 10 minutes at RT. The supernatant containing all the cellular proteins was collected, quantified and ~100 µg of protein sample was employed for proteome analysis. For performing mass spectrometry, proteins in the cell lysates were reduced with 20 mM dithiothreitol (DTT) and incubated at 95°C for 10 minutes. Further, the sample was alkylated with 40 mM iodoacetamide in dark for 30 minutes to block free cysteine residues. The alkylation reaction was quenched by adding 10 mM DTT. Trypsin was added at a ratio of 1:50 (trypsin: lysate) and the samples were incubated at 37°C overnight. Digested sample was cleaned by using a C18 silica cartridge column to remove the salt followed by drying using a speed vac vacuum concentrator at RT.

Peptides (~2 µg) from each sample were analyzed by reverse phase nano LC–MS/MS by using easy-nLC 1200 interfaced with a Q-exactive orbitrap mass spectrometer (Thermo Fisher Scientific). Samples were loaded onto a packed 75cm x 50cm PepMap RSLC C18 2µm column (Thermo fisher scientific) by using mobile phase A (2% Acetonitrile + 98% water with 0.1% Formic acid) and mobile phase B (80% Acetonitrile + 20% water with 0.1% Formic acid). All samples were eluted from the analytical column at a flow rate of 300 nL/min by using a linear gradient of 5% solvent B to 45% solvent B over a duration of 104 min, followed by linear gradient of 45–90% of solvent B for 1 min. The column was regenerated by washing with 90% solvent B for 10 min and re-equilibrated with 5% solvent B for 3 min. Mass spectrometry data was acquired by using a data-dependent acquisition procedure and intact peptides were detected in the orbitrap at a resolution of 70,000 and a scan range of 350−2,000 m/z. Peptides were selected for MS/MS and ion fragments were detected in the orbitrap at a resolution of 17,500 in a scan range of 200−2,000 m/z.

Quantitative and qualitative identification of all the expressed proteins upon infection was performed using Proteome Discoverer 2.4 (Thermo Fisher Scientific). The output file with protein levels represented by Sequest HT along with its annotation from UNIPROT database (for Homo sapiens, 202195 entries, October 2021) was subjected to normalization and differential proteome identification. Trypsin was employed as a protease with a maximum of two missed cleavage sites allowed. The mass tolerance for peptides was set to 10ppm and mass tolerance for fragment ions was set to 20mmu. Carbamidomethylation of cysteines was used as fixed modification, and oxidation of methionines, acetylation of lysine and histidine were used as variable modification. Peptides with only high confidence (target peptide FDR- 0.01) were used and minimum of one unique peptide was considered for successful protein identification. Quantitative proteomics analysis was carried out by using amica (69) web-based tool for quality control, differential expression, biological network and over-representation analysis. The replicate experiment data was analyzed for reproducibility by PCA and unsupervised correlation condition tree. Further, the differential proteome analysis was performed by comparing infected with uninfected proteome as well as Rv infected proteome with Ra infected proteome profiles. edgeR was used to perform DPA (differential proteome analysis) with a fold change of 2 and above with a FDR (false discovery rate) of pValue <0.05. Unsupervised hierarchical clustering of DEPs was performed by using Cluster 3.0 and visualized using java tree view to identify the up and down-regulated protein clusters across the conditions compared. The DEPs were also visualized using volcano plot to understand the magnitude of change in protein expression as induction or repression.

The DEPs were further subjected to GO and pathway analysis using DAVID online tool with a FDR criterion of pValue <0.05 to identify enriched pathways and gene ontology categories. SRPlot (70) was used to plot the DEP results for better understanding of the experimental changes. Statistically significant and biologically relevant gene ontology terms and pathways along with protein-protein interaction data of the DEPs were provided as input to RegNet algorithm (Theomics International Pvt. Ltd.). RegNet algorithm identifies the connecting nodes and edges from the raw input and derives the list of connections (gene-pathway-condition), enriched in the overall experiment. Further, this information was provided as an input to CytoScape V 2.8.2 (National Institute of General Medical Sciences by National Institutes of Health) to visualize the network. Force-directed spring-embedded layout algorithm was applied to the network and nodes were sized based on their connectivity score with larger nodes bearing the highest score.

Real-time PCR

Total RNA was isolated from all the three groups employed in the study (M. tb H37Rv infected hBM-MSCs, M. tb H37Ra infected hBM-MSCs and uninfected hBM-MSCs) by using Direct-zol RNA Miniprep kit (Zymo research) as per the manufacturer’s protocol. Briefly, 1ml TRIzol reagent (Invitrogen) was added into the wells to lyse the cells followed by loading of the entire lysate onto the RNA columns. The columns were washed by using RNA pre-wash and the samples were eluted from the columns in DNA/RNA-free water. The integrity of RNA was evaluated by using nano-drop machine. Total RNA (~2µg) was converted to cDNA by using SuperScript IV VILO reverse transcription kit (Thermo Fisher Scientific) according to the manufacturer’s protocol and gene specific primers for all the candidate genes were designed by using 'Primer 3' software (the primer sequences are mentioned in table 1). Primers were procured (Merck) and the real time PCR reaction assays were performed in a total reaction volume of 10µl by using PowerUp SYBR Green Master Mix (Applied Biosystems). The qPCR cycles were carried out under standard cycling conditions (stage 1: initial denaturation at 95°C for 10mins, stage 2: consisting of 40 cycles of denaturation at 95°C, for 15 sec followed by annealing, extension and fluorescence reading at 60°C for 1 min and stage 3: hold at 4°C). The experiment was performed by using independent replicates and ΔCt values were determined relative to GAPDH expression.

Statistical significance

MS-based proteome analysis were performed for three groups (M. tb H37Rv infected hBM-MSCs, M. tb H37Ra cells infected hBM-MSCs and uninfected cells) separately in three independent replicates. The total of nine samples were processed and analyzed by a reverse phase nano LC–MS/MS by using easy-nLC 1200 interfaced with a Q-exactive orbitrap mass spectrometer. Further, qualitative and quantitative identification of all the expressed proteins was performed using Proteome Discoverer (version 2.0) and amica web-based tool. edgeR was used for differential proteome analysis, GO and pathway analysis was performed using DAVID online tool and protein-protein interaction was studied using RegNet algorithm. Statistical significance was performed by using Student's t test and a fold change of 2 and above with a false discovery rate of pValue <0.05 was defined as cutoff in all analyses. The growth kinetics of M. tb H37Rv and M. tb H37Ra was analysed by plotting a graph using GraphPad Prism. The data is represented as the mean ± SEM (error bars) of at least two independent experiments (*, p < 0.05; (**, p < 0.01; ***, p < 0.001, two-way ANOVA, Bonferroni post-tests).

Data availability

All the mass spectrometry raw data has been deposited at the ProteomeXchange consortium via the MassIVE partner repository (PXD050144). Data submitted to MassIVE (accession number- MSV000094167) can be accessed by using Username: MSV000094167_reviewer; Password- Gk.mtb123).

Acknowledgements

We acknowledge BSL3 facility at the University of Delhi South Campus (UDSC), New Delhi, India for providing necessary facilities for conducting experiments related to the use of M. tb.We thank UDSC-CIF for the mass spectrometry and confocal services. We are also thankful to UDSC-Microarray facility and Prof. Amit Gupta for providing us generous access of equipment for conducting real-time PCR studies. We acknowledge Prof. Anil K. Tyagi and Dr. Prachi Nangpal for critical reading of the manuscript. We are thankful to Apoorva Mishra for providing help in preparation of the figures related to analysis of proteomics data.

Author contributions

S.K. and N.A. conducted the experiments. S.K. and N.A. analysed the data. M.V. analysed the proteomics data using bioinformatics. S.K. wrote the first draft of the manuscript. N.A. and G.K. wrote the final draft of the manuscript. G.K. conceived the study, provided overall supervision, and acquired funding for the study.

Funding statement

This study was financially supported by DU-IoE (Grant no. IoE-DU/MRP/2022/056), SERB, Department of Science and Technology, Government of India (CRG/2018/003325), UGC-SAP, and DU intramural funds. S.K. and N.A. received senior research fellowship from the Council of Scientific and Industrial Research, New Delhi, India.

Declaration of interests

The authors declare no conflicts of interest.

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Table 1: Differentially expressed protein of hBM-MSCs in response to M. tb H37Ra and M. tb H37Rv.

*Log2FC <-2 or > 2, P<0.05.
Groups	Total no. of differentially expressed proteins (DEPs)	No. of up-regulated proteins	No. of down-regulated proteins
Rv Vs UI	200	72	128
Ra Vs UI	168	95	73
Rv Vs Ra	141	33	108

Table 2: List of the primer sequences employed for real time PCR study.

Name	Forward primer (5’-3’)	Reverse Primer (5’-3’)
CXCL-10	CCACGTGTTGAGATCATTGC	TGCTCCCCTCTGGTTTTAAG
MMP-13	TTGAGCTGGACTCATTGTCG	GATTCCCGCGAGATTTGTAG
COL1A2	TTCTGCAACATGGAGACTGG	AATCCATCGGTCATGCTCTC
CLECB3	CCAGAAGCCCAAGAAGATTG	GGCTCTTGAGCTCCTCAAAC
GREM-1	CTTGGCCACCTCTCTTTTTG	ATGGGTGTGGCTTTTCTGAG
UQCRH	CGAGCAAAAGATGCTTACCG	CGGGCCTTTACACATTTCTC
GPX-1	CGCCAAGAACGAAGAGATTC	CTCGAAGAGCATGAAGTTGG
HNRNPK	AACGCCCTGCAGAAGATATG	GCCTCCTTTTCCAATCACTG

No competing interests reported.

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You are reading this latest preprint version

Global proteomics reveals pathways of mesenchymal stem cells altered by Mycobacterium tuberculosis.

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Abstract

Figures

Introduction

Results

Confocal microscopy of hBM-MSCs infected with M. tb

Discussion

Methods

Culturing of cells

Infection of hBM-MSCs with M. tb

Growth kinetics of M. tb inside hBM-MSCs

Label free mass spectrometry based proteomics

Statistical significance

Declarations

Declaration of interests

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1