[* Joint first authorship] [Authors in our group]
Hill AL, Rosenbloom DIS, Nowak MA, Siliciano RF (2018). Insight into treatment of HIV infection from viral dynamics models. Immunological Reviews. Sep 1;285(1):9–25. +details
This review is part of a special issue on "Modeling Viral Infection and Immunity", organized by Alan Perelson and Ruy Ribiero. The odds of living a long and healthy life with HIV infection have dramatically improved with the advent of combination antiretroviral therapy. Along with the early development and clinical trials of these drugs, and new field of research emerged called viral dynamics, which uses mathematical models to interpret and predict the time-course of viral levels during infection and how they are altered by treatment. In this review, we summarize the contributions that virus dynamics models have made to understanding the pathophysiology of infection and to designing effective therapies. This includes studies of the multiphasic decay of viral load when antiretroviral therapy is given, the evolution of drug resistance, the long-term persistence latently infected cells, and the rebound of viremia when drugs are stopped. We additionally discuss new work applying viral dynamics models to new classes of investigational treatment for HIV, including latency-reversing agents and immunotherapy.
This review is part of a special collection entitled "Progress in Achieving Long-Term HIV Remission". It summarizes work during the period of 2016-2018 related to using mathematical models to better understand the mechanisms of persistence of HIV despite antiretroviral therapy, and to design new therapies to cure infection.
Lim S-Y, Osuna CE, Hraber PT, Hesselgesser J, Gerold JM, Barnes TL, Sanisetty S, Seaman MS, Lewis MG, Geleziunas R, Miller MD, Cihlar T, Lee WA, Hill AL, Whitney JB (2018). TLR7 agonists induce transient viremia and reduce the viral reservoir in SIV-infected rhesus macaques on antiretroviral therapy. Science Translational Medicine. May 2;10(439):eaao4521 (PubMed). +details
Anti-HIV drugs must be taken for life, because latent (dormant) virus persists indefinitely and will restart the infection if treatment is stopped. Scientists are searching for new therapies that will permanently cure the infection, either by perturbing latent virus or boosting the immune system's ability to control reactivating virus. This study, which was lead by James Whitney at Harvard's Center for Virology & Vaccine Research, tested out a new immunotherapy in the primate model of HIV (SIV). The therapy involved a small-molecule drug developed by Gilead Sciences that stimulates the TLR7 receptor of the innate immune system, and was given to animals who while they were on antiretroviral drugs. This study found that the drugs completely prevented viral rebound in some animals, and altered it in others. We used mathematical models to help understand what the mechanism of action of these drugs were, based on the patterns of viral rebound.
Wang Z, Gurule EE, Brennan TP, Gerold JM, Kwon KJ, Hosmane NN, Kumar M, Beg S, Capoferria AA, Ray SC, Ho YC, Hill AL, Siliciano JD, Siliciano RF (2018). Expanded clones carrying replication-competent HIV-1 persist, wax, and wane. PNAS. February: 201720665. doi:10.1073/pnas.1720665115 (PubMed) +details
A major barrier to curing HIV is the long-term persistence of latent virus in memory T cells. It is not completely understood how this "reservoir" of latently infected cells last for up to decades during antiretroviral therapy. This study, lead by Bob Siliciano's lab, examined the genotype and phenotype of the latent reservoir over time in a cohort of treated patients. They found that there are many genetically identical infectious viruses archived in cells and that the population shifts over time. Because of the very high mutation rate of HIV during active infection and the lack of active infection during treatment, finding genetically identical latent viruses suggests that latently infected cells can proliferate without "waking up", and that this contributes to their persistence. This was confirmed with cell culture experiments that stimulated cells to proliferate. We designed and implemented statistical tests to compare the changes in viral populations over time to what would be expected just by chance due to random sampling. Overall, this study contributes to the idea that latency may be a more dynamic phenomenon than originally thought.
Neagu IA, Olejarz J, Freeman M, Rosenbloom DIS, Nowak MA, Hill AL (2018). Life cycle synchronization is a viral drug resistance mechanism. PLoS Computational Biology. 14: e1005947. doi:10.1371/journal.pcbi.1005947 (PubMed). +details
Virus such as HIV, Hepatitis B and C, and influenza are a major source of illness and death worldwide. As the availability of targeted drug therapies to these infections has increased, so has the prevalence of drug-resistant strains. Usually, we think that drug resistance is caused by altering drug binding, but here we propose an alternative mechanism available to viruses. Using large-scale simulations of evolving viral populations, we show that regular patterns of drug intake select for viruses whose life cycle length is synchronized with the drug period. These strains can grow to high levels and cause therapy failure. We demonstrate this new type of resistance is robust to missed or mistimed pills, and realistic drug kinetics, but the degree of resistance depends most critically on the ability of the virus to control its life cycle across generations. More generally, we show that the common mathematical method of calculating the critical therapy efficacy needed to control infections fails under periodic antiviral dosing, and develop an alternative method. This finding suggests that existing tests for drug-resistant virus may miss a major pathway: genotypic tests often only look for mutations in viral proteins bound by the drug, not those controlling lifecycle, and phenotypic tests are always conducted in the presence of constant drug levels, not physiologically-relevant periodic levels. We hope this work will inspire new experimental studies to test for life cycle synchronization in vivo and design more comprehensive screens for drug-resistant strains.
This chapter will appear in the forthcoming textbook "HIV Latency", edited by Guido Silvestri and Mathias Lichterfeld, and published by Springer. Viral latency is a major barrier to curing HIV infection with antiretroviral therapy, and consequently, for eliminating the disease globally. The establishment, maintenance, and potential clearance of latent infection are complex dynamic processes and can be best understood and described with the help of mathematical models. Here we review the use of viral dynamics models for HIV, with a focus on applications to the latent reservoir. Such models have been used to explain the multiphasic decay of viral load during antiretroviral therapy, the early seeding of the latent reservoir during acute infection and the limited inflow during treatment, the dynamics of viral blips, and the phenomenon of posttreatment control. In addition, mathematical models have been used to predict the efficacy of potential HIV cure strategies, such as latency-reversing agents, early treatment initiation, or gene therapies, and to provide guidance for designing trials of these novel interventions.
Kirtane AR, Abouzid O, Minahan D, Bensel T, Hill AL, Selinger C, Bershteyn A, Mo SS, Craig M, Mazdiyasni H, Cleveland C, Rogner J, Lee YAL, Booth L, Javid F, Wu SJ, Grant T, Bellinger AM, Nikolic B, Hayward A, Wood L, Eckhoff PA, Nowak MA, Langer R, Traverso G (2017). Development of an oral once-weekly drug delivery system for HIV antiretroviral therapy. Nature Communications, 9: 2. doi:10.1038/s41467-017-02294-6. +details
Antiretroviral therapy is very effective at suppressing HIV infection, but since it's not curative, pills must be taken every day for life. This makes it expensive and logistically challenging to get drugs to the millions of infected individuals around the world, and makes it hard for patients to consistently adhere to treatment. In this paper, a grouped of engineers led by Bob Langer and Gio Traverso at MIT developed a proof-of-concept device to allow for once-weekly oral delivery of antiretroviral drugs. We used mathematical models of HIV dynamics to understand how the altered drug-level trajectories with this drug-delivery strategy could impact treatment outcomes, including the likelihood of drug resistance. Our modeling framework can also be used to evaluate other "long-acting" antiretroviral strategies under development.
Current antiretroviral drugs dramatically suppress HIV levels in the body but cannot cure the infection. Low level virus persists despite years of treatment, and whenever drugs are stopped, the infection rapidly rebounds. There is debate in the field about the source of this persistent virus. Some believe that the drugs are not fully effective, and that virus continually replicates in some sanctuaries in the body. Others believe that the drugs fully suppress viral replication, but that long-lived latent virus can survive years of treatment. A 2016 Nature paper claimed to find evidence of ongoing replication and evolution in virus that persisted during treatment, supporting the claim of ineffective drugs. In this response paper, we show that problems with the experimental design and phylogenetic analysis used in that paper mean that false signals of evolution would be detected even in the absence of viral replication. More generally, we show that classic phylogenetic methods should be used with extreme caution when applied to populations with demographic processes not captured by the models underlying the inference procedures.
Borducchi EN, Cabral C, Stephenson KE, Liu J, Abbink P, Nkolola JP, Brinkman AL, Peter L, Lee BC, Jimenez J, Jetton D, Mondesir J, Mojta S, Chandrashekar A, Molloy K, Alter G, Gerold JM, Hill AL, Lewis MG, Pau MG, Schuitemaker H, Hesselgesser J, Geleziunas R, Kim JH, Robb ML, NL, Barouch DH (2016). Ad26/MVA therapeutic vaccination with TLR7 stimulation in SIV-infected rhesus monkey. Nature, 540 (7632), 284-287: doi:10.1038/nature20583 (PubMed) +details
Anti-HIV drugs must be taken for life, because latent (dormant) virus persists indefinitely and will restart the infection if treatment is stopped. Scientists are searching for new therapies that will permanently cure the infection, either by perturbing latent virus or boosting the immune system's ability to control reactivating virus. This study, which was a collaboration between Dan Barouch at Harvard's Center for Virology & Vaccine Research, the US Military HIV Research Program, and industry partners Gilead and Janssen, tested out a new immunotherapy in the primate model of HIV (SIV). The therapy involved a small-molecular drug that stimulates the TLR7 receptor of the innate immune system, and a vaccine, which were both given to animals who while they were on antiretroviral drugs. This study found that the drugs altered the kinetics of viral rebound in some animals, even leading a subset of them to fully control the infection after a brief rebound. We used mathematical models to help understand what the mechanism of action of these drugs were, based on the patterns of viral rebound.
Hill AL , Rosenbloom DIS, Siliciano JD, Siliciano RF (2016). Insufficient evidence for rare activation of latent HIV in the absence of reservoir-reducing interventions. PLoS Pathogens. Aug 25;12(8):e1005679. doi: 10.1371/journal.ppat.1005679. (PubMed) +details
HIV cannot be cured by current antiviral drugs, as it persists indefinitely in a latent form. When drugs are stopped, this latent virus can reactivate and restart infection. An important parameters that HIV researchers, in particular modelers, have been trying to estimate is how often a latently infected cells wakes up, because it determines how much the pool of latent virus would need to be reduced to delay or prevent the infection from rebounding. In this paper we debate the statistical methods that modelers have used to try to back out this pattern, and argue that reactivation of latency is likely to be more common than others have claimed, which makes the prospect of curing HIV by reducing latency bleak.
Hill AL, Rosenbloom DIS, Goldstein E, Hanhauser E, Kuritzkes DR, Siliciano RF, Henrich TJ (2016) Real-time predictions of reservoir size and rebound time during antiretroviral therapy interruption trials for HIV. PLoS Pathogens, 12(4):e1005535. doi:10.1371/journal.ppat.1005535. ( BioRxiv, PubMed ) +details
New therapies are being developed to permanently cure HIV infection. Many aim to reduce the pool of latent virus that persists despite years of treatment with antiretroviral drugs. Because latent virus is so difficult to sample and measure, often the only way to know if these new therapies have worked is to interrupt all treatment, and wait indefinitely to see if the infection rebounds. In this study we use a set of mathematical and statistical models to suggest optimal ways to design and interpret these treatment interruption trials. For various scenarios, we predict how long patients should be followed to be confident that they are cured, how frequent viral load sampling should occur, and how large clinical trials will need to be to estimate and compare drug efficacy. We demonstrate how to infer a range for number of remaining latent cells based on the timing of rebound after a long remission. As a case study, we apply these results to data from two HIV-positive patients who underwent bone marrow transplants and remained off treatment for months before suddenly rebounding. These findings can help inform the testing of new potentially-curative HIV therapies.
Moreno-Gámez S*, Hill AL*, Rosenbloom DIR, Petrov D, Nowak MA, Pennings P (2015). Imperfect drug penetration leads to spatial monotherapy and rapid evolution of multi-drug resistance. PNAS, 112(22):E2874-E2883. doi:10.1073/pnas.1424184112. (BioRxiv, PubMed) +details
The evolution of drug resistance is a major health threat. In chronic infections with rapidly mutating pathogens—including HIV, tuberculosis, and hepatitis B and C viruses—multidrug re- sistance can cause even aggressive combination drug treatment to fail. Oftentimes, individual drugs within a combination do not penetrate equally to all infected regions of the body. In this paper we used evolutionary dynamics models to suggest that this imperfect penetration can dramatically increase the chance of treatment failure by creating regions where only one drug from a combination reaches a therapeutic concentration. The resulting single-drug compartments allow the pathogen to evolve resistance to each drug sequentially, rapidly causing multidrug resistance. More broadly, our model provides a quantitative framework for reasoning about trade-offs between aggressive and moderate drug therapies.
Rosenbloom DIS, Elliott O, Hill AL, Henrich TJ, Siliciano JM, Siliciano RF (2015). Designing and interpreting limiting dilution assays: general principles and applications to the latent reservoir for HIV-1. Open Forum Infectious Diseases, 2(4):ofv123. doi:10.1093/ofid/ofv123. (BioRxiv, PubMed ) +details
Limiting dilution assays are widely used in infectious disease research. These assays are crucial for current HIV-1 cure research in particular, where they are used to quantify latent virus that persists despite antiretroviral treatment. In this paper we offer new tools to help investigators design and analyze dilution assays based on their specific research needs. The IUPMStats tool to analyze output from these assays is available online.
Laird GM, Bullen CK, Rosenbloom DIS, Martin AR, Hill AL, Durand CM, Siliciano JD, Siliciano RF (2015). Ex vivo analysis identifies effective HIV-1 latency–reversing drug combinations. Journal of Clinical Investigation. doi:10.1172/JCI80142 (PubMed) +details
Anti-HIV drugs can stop the virus from actively replicating but don't target latent virus, which can persist for a lifetime. New investigational drugs are being tested for their ability to rapidly "wake-up" latent virus and purge the infection from the body. This study evaluated a panel of such drugs in latently infected cells isolated from patients and tested their efficacy individually and in combination. We developed a mathematical model of latent HIV infection to make predictions about how results observed in the lab would translate to measurable outcomes in patients.
Leventhal GE*, Hill AL*, Nowak MA, Bonhoeffer S (2015). Evolution and emergence of infectious diseases in theoretical and real world networks. Nature Communications, 6 (6101); doi:10.1038/ncomms7101 (PubMed) +details
One of the most important advancements in modeling infectious disease spread has been the development of methods that account for realistic host population structure. The central finding is that heterogeneity in contact networks, such as the presence of ‘superspreaders’, accelerates infectious disease spread in real epidemics. Disease control is also complicated by the continuous evolution of pathogens in response to changing environments and medical interventions. It remains unclear, however, how population structure influences these adaptive processes. Here we examine the evolution of infectious disease in empirical and theoretical networks. We show that the heterogeneity in contact structure, which facilitates the spread of a single disease, surprisingly renders a resident strain more resilient to invasion by new variants. Our results suggest that many host contact structures suppress invasion of new strains and may slow disease adaptation. These findings are important to the natural history of disease evolution and the spread of drug-resistant strains
Hill AL*, Rosenbloom DIS*, Fu F, Nowak MA, Siliciano RF (2014). Predicting the outcomes of treatments to eradicate the latent reservoir for HIV-1. PNAS, 111 (37), 13475-13480. (Arxiv, PubMed) +details
HIV infection cannot be cured by current antiretroviral drugs, due to the presence of long-lived latently infected cells. New anti-latency drugs are being tested in clinical trials, but major unknowns remain. It is unclear how much latent virus must be eliminated for a cure, which remains difficult to answer empirically due to few case studies and limited sensitivity of assays for latent virus. In this paper, we introduce a mathematical model of HIV dynamics to calculate the likelihood and timing of viral rebound following anti-latency treatment. We derive predictions for the required efficacy of anti-latency drugs, and demonstrate that rebound times may be highly variable and occur after years of remission. These results will aid in designing and interpreting HIV cure studies.
Whitney JB, Hill AL, Sanisetty S, Penaloza-MacMaster P, Shetty M, Parenteau L, Cabral C, Shields J, Blackmore S, Smith JY, Brinkman AL, Peter LE, Mathew SI, Smith KM, Borducchi EN, Rosenbloom DIS, Lewis MG, Hattersley J, Li B, Hesselgesser J, Geleziunas R, Robb ML, Kim JH, Michael NL, Barouch DH (2014). Rapid establishment of the viral reservoir prior to systemic viremia following mucosal SIV infection of rhesus monkeys. Nature. 512 (7512): 74-77 (PubMed) +details
A small fraction of cells that HIV infects revert to a state of latency, where the virus can persist for years, despite antiretroviral treatment. This study investigated whether initiating antiretroviral treatment very early after infection could restrict the amount of latent virus formed, so that after some period of treatment, it could be stopped without the risk of infection rebounding. In a primate model of HIV (SIV), treatment as early as 3 days after infection did not prevent viral resurgence after treatment interruption. We used viral dynamics models to understand the relationship between time of treatment, reservoir size, and rebound kinetics when treatment was stopped. This study suggests that even with extremely early detection and intervention for individuals infected with HIV, antiretroviral therapy will not be curative.
Henrich TJ, Hanhauser E, Marty MF, Sirignano MN, Keating S, Lee T-H, Robles YP, Li JZ, Heisey A, Hill AL, Busch MP, Armand P, Soiffer RJ, Altfeld M, Kuritzkes DR (2014). Antiretroviral-free HIV-1 remission and viral rebound following allogeneic stem-cell transplantation: implications for HIV-1 cure research. Annals of Internal Medicine, 161(5):319-327 (PubMed) +details
To date we only know of one individual who was completely cured of HIV. Commonly known in the literature as the "Berlin patient", this HIV-positive individual also developed leukemia, and was treated with chemotherapy and a bone marrow transplant, which was received from a donor who had a naturally-occuring mutation rendering cells resistant to HIV infection. Despite remaining off antiretroviral therapy, no virus has been detected for almost a decade. While the high risk of this procedure and the rarity of HIV-resistant donors means this is not a practical solution to cure most people living with HIV, scientists want to understand how it worked to help design new treatments. It was unclear if the "Berlin patient" was cured due to the transplant procedure, which could have reduced latent virus, or the HIV-resistant cells. To help understand this cure, two other HIV-positive indiviuals requiring bone marrow transplants were studied. They could not be mathed with HIV-resistant donors, but they were able to stay on their antiretroviral drugs during the transplant. After the procedure they had no detectable virus, and eventually stopped therapy. Virus did not rebound, and for many months they appeared to be cured. However, they both eventually experienced sudden and rapid resurgence of the infection. This work showed that even dramatic reductions in latent virus could not revent eventual rebound, raising the bar for anti-latency therapy and confirming predictions of our earlier models.
Humplik J, Hill AL, Nowak MA (2014). Evolution of infectious diseases in finite populations. Journal of Theoretical Biology, 360 (149-162) (PDF, PubMed)+details
One of the most important quantities in infectious disease epidemiology is the basic reproductive ratio (R0) - defined as the average number of new infections caused by a single infected individual during its lifetime in an otherwise susceptible population. The magnitude of R0 determines how difficult it is to eradicate a disease, and in addition, models of competition for hosts between multiple disease strains conclude that evolution favors the strain with the highest R0. In this paper we show that this picture fails if we assume a finite population. Using a simple stochastic SIS model, we show that in general there is no analogous optimization principle. We find that successive invasions may in some cases lead to strains that infect a smaller fraction of the host population, and that mutually invasible pathogen strains exist. In the limit of weak selection we demonstrate that an optimization principle does exist, although it differs from R0 maximization. We show that this effect alters the outcomes of evolution in the presence of a trade-off between the virulence and the transmission rate of a pathogen.
Rosenbloom DIS*, Hill AL*, Rabi SA*, Siliciano RF, Nowak MA (2012). Antiretroviral dynamics determines HIV evolution and predicts therapy outcome. Nature Medicine, 18 (9) , 1378-1385. (PubMed) +details
We built a model for the evolutionary dynamics of HIV during antiviral drug treatment, which incorporated dose-response curves for a large panel of drugs and resistance mutants measured by a novel ex vivo assay developed in Bob Siliciano's lab at Johns Hopkins. This work showed that temporal variation in selection pressures during HIV treatment, due to drug pharmacology and imperfect patient adherence, is needed to explain drug resistance trends, and must be taken into account when designing dosing strategies. We were able to explain why patients can fail some drugs without developing resisance, and provide suggestions on how to optimize combination therapy.
Hill AL, Rosenbloom DIS, Nowak MA (2012). Evolutionary dynamics of HIV at multiple spatial and temporal scales. Journal of Molecular Medicine, 90 (5), 543-561. (PubMed) +details
This review paper was part of a special issue on evolutionary medicine. We discuss the critical role that evolution plays in the dynamics of HIV within and between hosts, including its original emergence from primate-specific ancestors, immune evasion and pathogenesis, the evolution of virulence, and de novo and transmitted drug resistance. We cover the role of mathematical models and of population genetics in understanding the infection.
Thankachan P, Kalasurmath S, Hill AL, Thomas T, Bhat K, Kurpad AV (2012) A mathematical model for the hemoglobin response to iron intake, based on iron absorption measurements from habitually consumed Indian meals. European Journal of Clinical Nutrition, 66 (4), 481-487. (PubMed)+details
In 2010 I spent a summer working at St. John's Research Insitute, an academic public health research center in Bangalore, India. In collaboration with nutritional researchers, I designed a model of iron regulation to help predict the effects of a particular iron intake on hemoglobin levels. Experimental results from the institute showed that iron absorption is a dynamic variable that depends on the current iron status of an individual, and their studies measured the specific values for typical South Indian meals. This and other experimental results and known physiological mechanisms for iron regulation were combined to construct a compartmental differential equation model for the feedback between iron status and absorption, and distribution between storage and hemoglobin compartments in the body. Importantly, this model suggests that recommended dietary allowance values for iron should not be solely based on achieving iron balance, since balance can be achieved for many intake values by regulating absorption and doesn’t guarantee a healthy hemoglobin level. The model can be used to predict hemoglobin recovery following blood loss, hemoglobin changes with increase or decreases in intake, and the effect of de- worming on hemoglobin levels.
Hill AL, Rand DG, Nowak MA, Christakis NC (2010) Infectious disease modeling of social contagion in networks. PLoS Computational Biology, 6 (11). (PubMed)+details
Information, trends, behaviors and even health states may spread between contacts in a social network, similar to disease transmission. However, a major difference is that as well as being spread infectiously, it is possible to acquire this state spontaneously. For example, you can gain knowledge of a particular piece of information either by being told about it, or by discovering it yourself. In this paper we introduce a mathematical modeling framework that allows us to compare the dynamics of these social contagions to traditional infectious diseases. We can also extract and compare the rates of spontaneous versus contagious acquisition of a behavior from longitudinal data and can use this to predict the implications for future prevalence and control strategies. As an example, we study the spread of obesity, and find that the current rate of becoming obese is about 2% per year and increases by 0.5 percentage points for each obese social contact, while the rate of recovering from obesity is 4% per year. The rates of spontaneous infection and transmission have steadily increased over time since 1970, driving the increase in obesity prevalence. Our model thus provides a quantitative way to analyze the strength and implications of social contagions.
Hill AL*, Rand DG*, Nowak MA, Christakis NC (2010) Emotions as infectious diseases in a large social network: the SISa model. Proceedings of the Royal Society B, 277 (1701). (PubMed) +details
Human populations are arranged in social networks that determine interactions and influence the spread of diseases, behaviours and ideas. In this paper we evaluate the spread of long-term emotional states across a social network. We introduce a novel form of the classical susceptible–infected–susceptible disease model which includes the possibility for ‘spontaneous’ (or ‘automatic’) infection, in addition to disease trans- mission (the SISa model). Using this framework and data from the Framingham Heart Study, we provide formal evidence that positive and negative emotional states behave like infectious diseases spreading across social networks over long periods of time. The probability of becoming content is increased by 0.02 per year for each content contact, and the probability of becoming discontent is increased by 0.04 per year per discontent contact. Our mathematical formalism allows us to derive various quantities from the data, such as the average lifetime of a contentment ‘infection’ (10 years) or discontentment ‘infection’ (5 years). Our results give insight into the transmissive nature of positive and negative emotional states. Determining to what extent particular emotions or behaviours are infectious is a promising direction for further research with important implications for social science, epidemiology and health policy. Our model provides a theoretical framework for studying the interpersonal spread of any state that may also arise spontaneously, such as emotions, behaviours, health states, ideas or diseases with reservoirs.
Aptekar JW, Cassidy MC, Johnson AC, Barton RA, Lee M, Ogier AC, Vo C, Anahtar MN, Ren Y, Bhatia SN, Ramanathan C, Cory DG, Hill AL, Mair RW, Rosen MS, Walsworth RL and Marcus CM (2009) Silicon nanoparticles as hyperpolarized magnetic resonance imaging agents. ACS Nano, 3 (12), 4003- 4008. (PDF, PubMed) +details
Magnetic Resonance Imaging (MRI) is one of the most powerful and safe medical imaging modalities, but the contrast achieved in images is limited to certain types of anatomical differences in tissues. A future vision for medical imaging is that targeted molecular probes could be designed to hone to any type of biomarker and allow it to be detectable at low concentrations by non-invasive imaging. Magnetically active nanoparticles have been developed for this purpose, but their signal is difficult to quantify, has low signal-to-noise, and is hard to distinguish from other causes of image contrast. This project was a collaboration between the laboratories of Ron Walsworth (Harvard Physics), Charlie Marcus (Harvard Pyhsics), and Bruce Rosen (MGH Martinos Center) to develop silicon-based molecular imaging probes for MRI. This technique is based on the resonance signal from the naturally-occuring 29-Si isotope, which can be enhanced before administration by a technique known as hyperpolarization. As a rotation student, I contributed to manufacturing and characterizing the magenetic resonance properties of the silicon nanoparticles.
Allard JF, Hill AL, Rutenburg AD (2007) Heterocyst pattern without patterning proteins in cyanobacterial filaments. Developmental Biology, 312 427-434. (PDF, PubMed)+details
The evolution of multicellular organisms depends on genetically identical cells performing specialized functions. A 3.5 billion-year-old example of this is filamentous cyanobacteria, or “blue-green algae”. When starved of fixed nitrogen, a regular pattern of cells differentiate to become specialized nitrogen-fixing “heterocysts”. Experiments have identified a number of pattern forming proteins, but even without these proteins the pattern is not entirely random. As a summer student with Andrew Rutenberg at Dalhousie University, I helped developed a model heterocyst formation; showing that stochastic cell growth and slow nitrogen diffusion are important factors in establishing the observed patterns.