Figure 1. in vitro and in silico model
Sepsis is the body’s dysregulated immune response to microbial invasion, or the body’s extreme response to infection. This immune dysregulation can cause a cascade of changes that can lead to systemic inflammation, damage to multiple organ systems, and eventually organ failure and death.There were approximately 49 million sepsis cases globally in 2017 with 11 million sepsis-related deaths accounting for 19.7% of all global deaths (WHO, 2023). Sepsis disproportionately affects vulnerable populations like newborns, pregnant women, and people living in low-income settings.
In the past two decades, there has been a consistent decline in in-patient mortality rates associated with sepsis (Zimmerman, 2013). However, the overarching prognosis for individuals diagnosed with sepsis remains largely unchanged. A significant portion of sepsis survivors endure prolonged stays in the Intensive Care Unit (ICU), with many ultimately succumbing to the complications of the condition. Recent data indicates a potential surge in sepsis-related mortalities (Prest, 2022). This is disconcerting, as it contrasts with the general positive trajectory observed in ICU patient outcomes, suggesting that the improvements in healthcare may not be benefiting sepsis patients equivalently. To bridge this evident disparity in patient outcomes, there is an imperative need for an enhanced understanding of the immunopathology underlying sepsis, coupled with the development of refined clinical tools and methodologies.
Septic shock involves systematic inflammation of the immune system and the release of pro-inflammatory mediators such as cytokines and various immune cells. While researchers often focus on the dysfunctional immune response, bone marrow plays a crucial role in the pathophysiology of sepsis. Bone marrow is a specialized tissue that is the primary site for hematopoiesis and helps regulate or mobilize immune cells. Specific regions of bone marrow known as hematopoietic niches create a microenvironment necessary to develop, differentiate, and mature blood cells, which is disrupted in septic conditions. When humans fight infection, they proliferate both myeloid and lymphoid progenitor cells in peripheral blood and boost local immune response, which is imperative to understanding the progression of sepsis in patients.
Predicting the clinical outcome of a sepsis diagnosis is difficult, as the effects can be chronic, early death, or rapid recovery based on the patient’s type of infection or underlying conditions. The signs and physical manifestations vary drastically because each patient responds to infection differently. The complexity of the human immune environment and the need for fast-acting medical care when afflicted makes generating data concerning sepsis immune response nuanced and complicated.
The immune-pathology of sepsis is still unknown because there are no models to study the molecular and cellular mechanisms of sepsis that address the dynamical changes of heamtopoietic niches and corresponding clinical outcomes. There is a particular need for an accurate preclinical model that can predict the disease progression of sepsis without harming human patients.
There has been a significant amount of research conducted on rat models in order to gain a deeper understanding of precise cellular responses resulting from sepsis, but there has not been a large amount of research done on human models. Animal models have had some success regarding the understanding of the effects of sepsis on hematopoietic stem cells (HSCs), and epigenetic regulation of HSCs has been noted on an elementary level. However, these animal studies present physiological issues, as animal models are too different from human models to make definitive conclusions regarding human HSC immune response to sepsis.A model that resembles human immune response is needed.
The primary method of characterizing sepsis and studying sepsis pathophysiology has been through the use of patient volunteers in hospitals. This method is beneficial as it allows for more physiologically accurate examinations of sepsis. However, sepsis research conducted using patient volunteers presents issues with experimental control and frequency, especially with limited access to patients with sepsis who are willing to take part in a scientific study. Furthermore, there are a slew of ethical issues associated with using human volunteers for studying sepsis. The need for rapid enrollment of human volunteers compounded with varying levels of patient acuity, depending on the severity of the case, creates problems in obtaining informed consent. Similarly, there are limited numbers of personnel available to conduct informed consent. The lack of human specificity in animal models and the experimental issues in volunteer models leave a lot to be desired in terms of developing an in vitro experimental model for studying sepsis.
Although research into organoid system technology for HSCs remains limited, there has been progress in the development of organ-on-chip technology. However, these are not adequately suited for sepsis research due to the omission of critical cell types. While organ-on-chip technology replicates organs using fabricated devices, organoid systems emulate organs by differentiating stem cells to produce all the essential components of the targeted organ. Consequently, organoid systems offer greater relevance for sepsis research, encompassing all cell types necessary to accurately depict the immune response dynamics upon external disturbances.
In summary, previous research and mechanistic models have attempted to analyze the patterns in HSC production and the resulting immune system response, but these methods fail to mimic human physiology and therefore cannot provide an effective model applicable to humans.
Our team has developed a multifaceted approach combining wet and dry lab models to study sepsis mechanisms, which can be used as a clinical tool in the future. Inspired by previous research using organoids as disease models (Khan, et al., 2023) our team has decided to create a human bone marrow organoid to mimic the bone-marrow environment in-vitro to lay the foundation for further immune and sepsis related studies. In conjunction, to further our understanding of the immune system and septic conditions, we built a mechanistic model to simulate and predict hematopoeietc dynamics.
Through a series of stepwise, directed-differentiation steps, we will recapitulate bone-marrow conditions in-vitro that display key features of the endosteal and perivascular niche of bone marrow, including myeloid cell lineages affected by sepsis to study the effects of hematopoiesis and immune response in sepsis. The structural and chemical similarity of our organoids to human bone-marrow will allow for further studies of the immune system and septic conditions without harming a living test subject.
Figure 1. in vitro and in silico model
To further our understanding of the immune system and septic conditions, we also built an in silico mechanistic model This model allowed us to simplify the complex immune system through differential equations by treating the immune system as a set of nodes that each have a positive or negative “force” on the other nodes. Our model differs from other attempts in literature because it takes into account the number of hematopoietic stem and progenitor cells (HSPCs) along with pro-inflammatory leukocytes and anti-inflammatory leukocytes. Integrating HSPC’s into our model has given us insight into the nature of how the level of stem cells in our immune system can affect the overall immune response.
Our model has shown predicted trends of the immune system given varying starting conditions. Based on previous literature, we have produced trends for steady-state without pathogen insult, a healthy person with moderate pathogen insult (recovery), sepsis early death, and chronic sepsis. These predicted results have produced a dynamic system that can be used to explore other trends in an immune response by changing other initial values.
Our in vitro model in combination with our in silico model can produce trends that recapitulate the nature of sepsis progression in a patient. The in vivo model can inform our in silico model by showing our predicted trends, and giving a real world example of certain rates. Right now, our in silico model emulates our expected trends, but coupling it with the data of our in vitro model, we can determine their rates relative to each other. For example, if the growth rate of Inflammatory Leukocytes is three-fold that of Anti-inflammatory Leukocytes in our in silico model, but then we discover that it’s only two fold in the in vitro counterpart, then we can tune our in silico model to reflect these findings. The in silico model can inform the in vitro model by providing hypotheses to test based on what the in silico model predicts. For example, if the in silico model showed a specific trend given a certain challenge (i.e. PAMPS level), then one can use this information to predict that same trend when giving that challenge to the in vitro model. If there is any discrepancy, then this can lead to furthering the validity of the in silico model.
Both our in-vitro and in silico model can be used in a variety of ways, as one is able to adjust the initial values of various immune cells in the system, and see what trends may result from those different levels. This can help researchers explore different hypotheses for what trend they believe they would see if they were to increase or decrease the levels of some immune force from an established (though arbitrary) baseline. Using this in combination with our in vitro model, doctors could create a ‘digital twin’ of their patient. Doctors could create an organoid model of their patient, match the in silico model to the in vitro rates, and have a personalized in silico model that can be used to predict the outcome of the patient’s sepsis.
1. World Health Organization (2023, July 19). Sepsis. World Health Organization. Retrieved July 21st 2023 from https://www.who.int/news-room/fact-sheets/detail/sepsis#:~:text=Key%20facts,all%20global%20deaths%20.
2. Zimmerman, J., et al., (2013, April 27). Changes in hospital mortality for United States intensive care unit admissions from 1988 to 2012. Critical Care, 17(2): R81. Doi: doi: 10.1186/cc12695
3. Prest, J. et al. (2022, October). Sepsis-Related Mortality Rates and Trends Based on Site of Infection. Critical Care Exploration, 4(10). doi: 10.1097/CCE.0000000000000775
4. Nimmanagoti, N. et al. (2023, July 6). Bone Marrow Changes in Septic Shock: A Comprehensive Review. Cureus. 15(7). Doi:10.7759/cureus.42517
5. Khan, A. et al., (2023, Febuary 6). Human Bone Marrow Organoids for Disease Modeling, Discovery, and Validation of Therapeutic Targets in Hematologic Malignancies. Cancer Discovery. 13(2):364-385. doi: 10.1158/2159-8290
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