Lower respiratory tract infections, which include pneumonia, influenza, bronchitis, and bronchiolitis, are a significant global health concern and rank as the fifth leading cause of death worldwide (Troeger et al., 2017). Among these, influenza notably contributes to the burden of lower respiratory tract infections (Feldman and Shaddock, 2019). Historical data from the United States shows that, between the 1979-1980 and 2000-2001 seasons, H3N2 influenza A virus (IAV) led to the most hospitalizations and deaths (Thompson et al., 2003; Thompson et al., 2004). Notably, in Turkey’s 2015-2016 season, the fatality rate of H3N2 IAV exceeded that of H1N1 IAV (Tekin et al., 2019), emphasizing the significant threat of the H3N2 strain.

Various risk factors heighten the susceptibility to acute or severe lower respiratory tract infections. These risks encompass aging, existing health conditions, weakened immunity, smoking, incomplete vaccination, and socio-environmental factors such as overcrowding and malnutrition (Thompson et al., 2004; Lozada-Requena and Nunez Ponce, 2020). Aging particularly impacts both innate and adaptive immunity, primarily through toll-like receptors (TLRs) and the programmed death 1 (PD-1)/programmed death-ligand 1 (PD-L1) pathways (Lages et al., 2010; Shaw et al., 2011; Schneider et al., 2021). TLRs are essential in identifying pathogen-associated and damage-associated molecular patterns, empowering innate immune cells to counteract microbial invasions and activate the inflammasome (O'Neill et al., 2013; Hoque et al., 2014). Previous research has identified a notable decrease in TLR agonist response after the age of 65 (Zareian et al., 2019). Conversely, the PD-1/PD-L1 pathway, an inhibitory mechanism, preserves immune response equilibrium and immunotolerance. However, its excessive activation during cancer or viral infections can suppress T cell activity and inflammasome activation (Ai et al., 2020; Zhang Q. et al., 2020; Duhalde Vega et al., 2022). Modulating the PD-1/PD-L1 pathway offers potential therapeutic interventions for viral infections and immune-related disorders (Chamoto et al., 2017).

Furthermore, the age-associated decline in immune function, known as immunosenescence, augments vulnerability to infections (Rodrigues et al., 2021). As an example, our prior research identified differences in H7N9 IAV replication between younger (21-64 years) and older (≥ 65 years) individuals (Huang et al., 2018). Besides aging, comorbidities like lung cancer (Yu et al., 2016) and hypertension (Nunes et al., 2019) potentially influence TLRs and the PD-1/PD-L1 pathways, further contributing to immunosenescence (Ferrara et al., 2017). This compromised immune function makes individuals more susceptible to viral and bacterial infections. Yet, the comprehensive influence of patient-specific factors on H3N2 IAV infection remains relatively unexplored.

In this study, we set out to: (1) assess the effects of H3N2 IAV on primary lung tissue cultures, emphasizing TLRs, the PD-1/PD-L1 pathway, and other immune biomarkers, and (2) determine the role of patient characteristics, especially age, in H3N2 IAV infection using an ex vivo lung tissue model. We theorized that specific patient traits might impact the immune response during the early stages of ex vivo H3N2 IAV infection. Our exploration aims to clarify the intricate relationships between patient characteristics, immune responses, and H3N2 IAV infection, potentially guiding personalized influenza treatment strategies.

The findings from our investigation amplify the immense value of utilizing lung explant tissue cultures as an advanced model to dissect the complexities inherent to viral infections. Prioritizing human explant tissues in our approach has enriched our perspective, casting a wider net over immunological dynamics that encompasses a myriad of immune cells and their respective microenvironments. This level of granularity and breadth has been notably absent in earlier studies.

In the context of in vivo infections, the IAV, as corroborated by previous research, predominantly targets airway epithelial cells initially (Portela and Digard, 2002). This targeting is directly responsible for a cascade of events leading to viral replication, its subsequent release, and the eventual manifestation of clinical symptoms. The next crucial line of defense, the airway macrophages, which are at the heart of innate immunity, are quick to identify and counter the advancing IAV infection (Meischel et al., 2020). What makes our study stand out is how we exposed both these airway cells and the macrophages to the H3N2 virus at the same time. This unique approach helps us understand better how the body’s initial defense mechanisms, especially the activation of certain macrophages, respond to the virus. Our method offers a promising way to study how the virus affects humans, how our bodies react to it, and how to develop treatments against the H3N2 virus, potentially reducing the severity of flu symptoms (Hocke et al., 2017). This model can also help improve the way we test new treatments for their effectiveness against the virus. Moving forward, we’ll explore more about how the immune system responds, how the virus behaves in different immune cells, and how individual differences in patients can change these results.

T cells hold a pivotal position in the intricate tapestry of our body’s immune defense mechanisms. Triggered into action by antigenic presence, they not only mobilize to the lungs but also synthesize key cytokines, predominantly IL-2 and IFN-γ. These cytokines have a propensity to amplify cellular proliferation and augment other cellular functionalities, which can cascade into inflammatory responses (Jagtap, 2018). Our investigative journey illuminated the intricate interplay between TLRs, the PD-1/PD-L1 pathways, and their influence on cytokine concentrations and viral NP expressions within immune cells. A salient revelation from our exploration was the amplified PD-L1 expression in macrophages during the nascent stages of H3N2 IAV infection, which harmonizes with findings from a preceding study (Staples et al., 2015). Of noteworthy mention was the discerned positive association between the variations in PD-L1 expression on epithelial cells and the corresponding variations in PD-1 expression on CD3⁺/CD4⁺ T cells. The magnitude of this association’s importance cannot be overstated. Given that lung epithelial cells double up as both anatomical barricades and antigen presenters, their PD-L1 expression interacts with PD-1, imposing a regulatory mechanism on lung CD4⁺ resident memory T cells, thus modulating barrier immunity (Shenoy et al., 2021). Viral onslaughts, more often than not, excessively stimulate the PD-1/PD-L1 pathways, which could attenuate T cell efficiency (Patil et al., 2017). A scenario wherein these T cells become overburdened, or “exhausted,” could compromise their combative efficacy against viral entities (Wherry, 2011). Hence, maintaining an equilibrium in the PD-1/PD-L1 pathway dynamics among epithelial cells, macrophages, and T cells, especially during the incipient phases of a H3N2 IAV infection, is of paramount significance. This equilibration ensures that our immune response remains vigilant and potent. The observed diminution in the secretions of IL-2 and IFN-γ among the geriatric demographic posits that PD-L1-expressing macrophages might wield greater influence in the phenomena of inflamm-aging (Sharma, 2021).

Our study highlights the relationship between immune responses and the interaction of IL-2 with the PD-1/PD-L1 pathways during H3N2 IAV infections. In simple terms, IL-2, distinguished by its dual pro-inflammatory and anti-inflammatory characteristics, stands out as an influential protagonist in the resistance against microbial incursions (Alam et al., 2020). In the setting of our study with human lung specimens, IL-2 unveiled its multifaceted role in orchestrating immune responses. It promotes the proliferation and potency of CD8⁺ cytotoxic T cells and natural killer cells, which are indispensable components of our immunological arsenal (Kamimura and Bevan, 2007). Concurrently, IL-2 has implications on regulatory T cells, ensuring a check on the immune system, and averting undue inflammatory reactions (Malek and Bayer, 2004). However, a compelling observation emanating from our study was the incongruity between IL-2 secretory levels and viral NP expression. This hints at the possibility that the orchestration of IL-2 secretion may be governed by external determinants, potentially tethered to T cell operational dynamics, especially in scenarios where macrophages manifest heightened PD-L1 expression. Rampant stimulation of the PD-1/PD-L1 pathway is intrinsically linked with T cell malfunction, culminating in compromised antiviral responses across a spectrum of viral incursions (Schonrich and Raftery, 2019; Zhou et al., 2019). Thus, the delicate balance between IL-2 concentrations and PD-L1 levels potentially plays a decisive role in steering T cell behavior amidst H3N2 IAV onslaughts.

A crucial context to consider here is that a considerable fraction of our tissue samples originated from patients diagnosed with lung cancer. The inherent characteristics of the tumor milieu must be factored into our interpretations. It is conceivable that within such a milieu, IL-2 is a harbinger signaling T cell exhaustion (Liu et al., 2021). However, there’s a glimmer of hope, as interventions inhibiting PD-L1 have showcased potential in revitalizing these fatigued T cells, potentially mitigating viral ramifications in certain infection contexts (West et al., 2013). We are thus led to postulate that a synthesis of elevated IL-2 levels combined with suppressed PD-L1 might be conducive for efficient viral clearance during the advanced phases of H3N2 IAV infections. To encapsulate, our findings point to the importance of IL-2 in the body’s fight against viral infections like H3N2 IAV. This molecule, with its dual roles, could be a promising target for future treatments, especially for influenza.

When juxtaposing our results derived from human lung tissue ex vivo infection models with those from animal studies, distinct differences emerge. For instance, in rat models, exposure to IAV antigens leads to an escalation in PD-1 expression in innate immune cells during acute lower respiratory tract infections. Concurrently, there’s a rise in PD-L1 expression, which appears to inhibit the action of CD8⁺ T cells (Erickson et al., 2012). Also, elevated levels of IFN-γ are linked to decelerated H3N2 IAV replication in these models, which might explain the subdued immune reactions commonly observed in the elderly (Hernandez-Vargas et al., 2014). However, our ex vivo model with human lung tissue provides potentially clarifying insights into these disparities. The prevalent presence of viral NP memory T cells – distinguished by their abundant multifunctional T cells and amplified cytokine output in adult human lungs – might be shaping the immune reactions we detected (Pen et al., 2014). Indications from our model hint at an accelerated release of inflammation-triggering factors steered by PD-L1 after H3N2 IAV infection compared to what has been observed in alternative models (Zhang J. et al., 2020). While animal studies have undeniably added immense value to our knowledge pool, they inherently have limitations in replicating the multifaceted nature of human immune responses. This is where our ex vivo model stands out. It offers an authentic window into human-specific reactions, enabling a direct examination of how human lung tissue counteracts H3N2 IAV infection. In doing so, our study illuminates the nuanced choreography of the immune system during human infections, potentially providing a foundation for more tailored therapeutic interventions.

In this study, several illuminating observations came to the fore. One of the most striking was the significant variability we observed in the % difference of PD-L1 expression on macrophages. Another intriguing finding was the correlation of aging with a muted increase in cytokines such as IL-2 and IFN-γ after controlling for potential confounding variables. However, aging was not found to be linked with TLR signaling or the PD-1/PD-L1 pathway. While earlier research posited that the decreased ability of CD8⁺ T cells to combat influenza in the elderly wasn’t due to a decrease in the frequency of virus-specific T cells (Boon et al., 2002), our findings hint at IL-2 secretion playing a possible role. This could be a contributing factor to the observed age-related diminishment in the effectiveness of CD8⁺ T cells against the H3N2 IAV, as reported in preceding studies (Zhou and McElhaney, 2011; Zhou et al., 2016). Consequently, our research adds a crucial layer of understanding to the evolving dialogue on age-related immunosenescence (Yoshikawa, 2000; Rodrigues et al., 2021). It underscores the importance of recognizing the delicate and complex balance of immune responses, especially against pathogens like the H3N2 IAV, and how these responses evolve with age. The revelations from this study not only inform future research directions but also point toward potential interventions to bolster immune responses, especially in our aging population.

Our detailed exploration into the innate immune responses and inflammasome activation post-ex vivo IAV infection has revealed intriguing patterns. By delineating our data into three distinct clusters: Cluster 1 (intermediate NP expression in macrophages and high secreted TNF-α level), Cluster 2 (low NP expression in macrophages and low secreted TNF-α level), and Cluster 3 (high NP expression in macrophages and intermediate secreted TNF-α level), we were able to discern specific molecular and cytokine response trends that shed light on how different patient groups may react to IAV exposure. In this context, Cluster 2 served as our reference subgroup.

Cluster 2, identified by its muted NP expression in macrophages during mock infections, likely represents individuals with limited previous exposure to IAVs. Their pronounced upswing in secreted cytokines TNF-α and IFN-γ upon H3N2 IAV exposure aligns with prior research (Miettinen et al., 2001; Seo and Webster, 2002), painting a picture of an immune system rallying its defenses against a relatively new viral threat.

In contrast, the pronounced NP expression in Cluster 3 during mock infections could signal a history of exposure to IAVs, possibly without overt clinical manifestations. This silent sensitization seems to have equipped them with a faster and more intense immune response upon subsequent H3N2 challenges (Gschoesser et al., 2002). The pronounced secretions of IL-2 and IFN-γ at the onset of H3N2 IAV exposure speak to this heightened immune vigilance.

Cluster 1, distinguished by its pronounced TNF-α secretion, unveils another facet of the immune response. With a demographic skew toward older individuals and those with a history of lung cancer, the heightened TNF-α secretion possibly hints at a backdrop of chronic inflammation, or even a predisposition toward malignant processes (Balkwill, 2006). This elevated TNF-α response, even in the absence of an active viral challenge, suggests underlying immune dysregulation. This observation, coupled with previous findings (Le Goffic et al., 2007), suggests that TLR3 overexpression on epithelial cells could be inducing IL-2, TNF-α, and IFN-γ upon IAV challenge. The amplified PD-L1 on macrophages, potentially facilitating viral proliferation (Ning et al., 2023), adds another layer to this narrative. When juxtaposed against Clusters 2 and 3, Cluster 1 exhibited a subdued cytokine response, possibly underpinning a hampered CD8⁺ T cell defense against IAV, especially in the older demographic (Liu et al., 2012). Taking together, our observations indicate that Cluster 1 individuals might be grappling with immunosenescence. This finding, in concert with the other cluster-specific observations, accentuates the multifaceted nature of the immune response to IAV and underscores the importance of individual patient characteristics in tailoring therapeutic strategies.

This study sheds light on the immune response and inflammasome activation during IAV infection using a human ex vivo model, but several caveats exist. First, we didn’t use a western blot for IAV NP in this study, but we had validated infections through quantitative real-time PCR of IAV RNA in our previous study (Huang et al., 2018). Elevated NP expressions typically indicate active IAV infection (Portela and Digard, 2002; Martinez-Colon et al., 2019). Second, prior research underscores the protective role of IFN-α against IAV in specific human tissues (Pothlichet et al., 2013; Matos et al., 2019). In light of existing evidence (Panda et al., 2010; McKendry et al., 2016; Galani et al., 2017) and our prior empirical observations (Huang et al., 2018; Hung et al., 2020), we strategically chose to employ flow cytometry for the identification of IAV NP, PD-L1, and TLR1-3 in this research. However, the implementation of Western blotting or quantitative PCR is indispensable for the accurate quantification of protein and mRNA levels of NP, PD-L1, and TLR1-3 in T-cells, macrophages, and epithelial cells, facilitating a more comprehensive understanding of host responses (Zhang Q. et al., 2020). We intend to incorporate these pivotal methodologies in subsequent studies to augment the depth and precision of our insights. Third, while our ex vivo model offers direct insights into human tissue responses, it inevitably lacks the systemic interplay present in in vivo conditions. This limitation means that while our findings provide foundational knowledge, in vivo studies will be essential for translating these observations into clinical practice. Fourth, our primary focus on CD3⁺ and CD8⁺ T cells may have missed the nuanced responses from other specialized T cell subsets. Including these subsets could help elucidate the full spectrum of T cell responses to IAV infection. Fifth, the relatively limited sample size and short incubation period may restrict the scope and generalizability of our findings. Future investigations employing larger sample sizes and prolonged incubation periods can offer more robust and detailed insights.

In conclusion, our study has illuminated the nuanced responses of human lung tissue to ex vivo H3N2 IAV infections, underscoring the central role of NP-expressing macrophages in the formative stages of the immune response. Aging, histories of lung cancer, and previous encounters with IAV emerge as pivotal factors that shape and modulate these responses. The molecular markers we’ve identified, notably NP expression in macrophages and TNF-α secretion during mock infections, offer a valuable schema to categorize patients based on the nature and magnitude of their immune reactions and subsequent inflammasome activations. Our ex vivo model stands out in its capability to mirror the myriad ways host factors mold innate immune responses to IAVs. This understanding, though preliminary, offers a bedrock upon which we can design more tailored and effective preventive and therapeutic interventions against H3N2 IAV and potentially other influenza viruses. To solidify our conclusions, studies with larger samples and a broader spectrum of immune cells are essential. This will enrich our understanding and improve strategies to manage IAV infections.

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding author.

The studies involving humans were approved by the Institutional Review Board at the Chang Gung Medical Foundation, Taoyuan, Taiwan. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

C-GH: Conceptualization, Data curation, Formal Analysis, Funding acquisition, Investigation, Methodology, Resources, Software, Validation, Writing – original draft. Y-CW: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Validation, Writing – original draft. M-JH: Data curation, Formal Analysis, Investigation, Methodology, Writing – review & editing. Y-JL: Data curation, Investigation, Methodology, Writing – review & editing. T-HH: Data curation, Investigation, Methodology, Writing – review & editing. P-WH: Data curation, Formal Analysis, Investigation, Methodology, Project administration, Validation, Visualization, Writing – original draft. S-LY: Data curation, Investigation, Methodology, Resources, Writing – review & editing. K-CT: Supervision, Writing – review & editing. S-RS: Supervision, Validation, Writing – review & editing. L-AL: Conceptualization, Data curation, Formal Analysis, Visualization, Writing – original draft.