Designing self-destructing bacteria to make effective tuberculosis vaccines

Working toward more effective tuberculosis (TB) vaccines, researchers at Weill Cornell Medicine have developed two strains of mycobacteria with “kill switches” that can be triggered to stop the bacteria after they activate an immune response. Two preclinical studies, published Jan. 10 in Nature Microbiology, tackle the challenge of engineering bacteria that are safe for use in controlled human infection trials or as better vaccines. While TB is under control in most developed countries, the disease still kills over a million people a year worldwide.

Spreading easily through the air, Mycobacterium tuberculosis can establish a chronic infection in human lungs, which can turn into a deadly respiratory disease. A safe vaccine called BCG, consisting of a weakened strain of the closely related Mycobacterium bovis, has been available for over a century but has limited efficacy.

“BCG protects children from tuberculosis meningitis, but it doesn’t effectively protect adults from pulmonary tuberculosis, which is why it’s only used in high-incidence countries,” said Dr. Dirk Schnappinger, professor of microbiology and immunology at Weill Cornell Medicine and a senior author on both of the new studies.

However, collaborators at the University of Pittsburgh and the National Institutes of Health’s Vaccine Research Center previously found that administering high doses of the BCG vaccine directly into the veins, instead of the usual route of giving it under the skin, was better at protecting adult macaque monkeys against lung infection.

Building a better vaccine

In one of the new papers, the team aimed to make this high-dose intravenous injection safer, without destroying the vaccine’s ability to stimulate a strong immune response. “We needed a version of BCG that triggers an immune response, but then you can flip a switch to eliminate the bacteria,” said Dr. Schnappinger.

After testing about 20 different strategies, the investigators found that lysins, enzymes encoded by viruses that can infect BCG, cause the bacteria to self-destruct. Using a clever bit of molecular engineering, they placed two different lysin genes under the control of gene regulators that respond to an antibiotic. By adding or taking away the antibiotic, they could then flip the kill switch.

“The lysins were known, but I don’t think they have been utilized as kill switches previously,” said Dr. Sabine Ehrt, professor of microbiology and immunology at Weill Cornell Medicine and a senior author on the papers.

With the newly engineered BCG, the researchers delivered high doses of the vaccine intravenously to antibiotic-treated macaques. When they stopped the antibiotic, the kill switch was activated, promptly ending the infection. The self-destructing bacteria released antigens that further stimulated the animals’ immune systems. The result was a robust immune response that protected the monkeys from subsequent lung infections with M. tuberculosis.

“Despite the promising preclinical results, evaluating if the vaccination actually works takes a long time and many people to test it. Tuberculosis doesn’t develop quickly and only in a small fraction of the people who are infected,” Dr. Schnappinger explained.

Such enormous, lengthy clinical trials can cost hundreds of millions of dollars, a major barrier to new vaccines. The urgent need for an effective TB vaccine has prompted researchers to find innovative ways to accelerate vaccine development.

3D imaging approach reveals intricate steps of herpes simplex virus assembly

A new combination of microscopy methods has revealed exquisite detail of the virus assembly process used by herpes simplex virus during replication.

The research, published today in eLife, is described by the editors as a fundamental study that comprehensively examines the roles of nine structural proteins in herpes simplex virus 1 (HSV-1) viral assembly. They say the thoroughly executed research yields compelling data that explain previously unknown functions of HSV-1 structural proteins.

Additionally, by integrating cryo-light microscopy and soft X-ray tomography, it presents an innovative approach to investigating viral assembly within cells that will be of broad interest to virologists, cellular biologists and structural biologists.

HSV-1 is a large virus that infects the mucous membranes of the mouth and genitals, causing life-long latent infections. The virus is composed of three layers—a capsid that contains the viral DNA, a protein layer called the tegument and an outer envelope that is studded with viral glycoproteins (proteins with a sugar attached). During replication, newly copied viral genomes are packaged up into this three-layer structure in a process called viral assembly.

While some drugs can block the virus’ DNA replication and alleviate symptoms, there is no permanent cure. A deeper understanding of the assembly process could inform the design of novel treatments or cures that inhibit virus formation.. But until now, pinpointing the role of different HSV-1 components in the viral assembly process has proved challenging.

“HSV-1 mutants that cannot make certain proteins have been used to study the role of viral genes in virus assembly, using a method called thin section transmission electron microscopy, or TEM,” says lead author Kamal Nahas, Beamline Scientist at Beamline B24, Diamond Light Source, Harwell Science & Innovation Campus, Didcot, U.K. “However, the extensive sample processing required for TEM can distort the microscopic structure and complicate the interpretation of features in viral assembly.”

Viral assembly involves a multi-step process, starting in the cell’s nucleus with assembly of capsids, packaging of the DNA to form “nucleocapsids,” and transport of these nucleocapsids out of the nucleus via a process of primary envelopment and de-envelopment to travel across the nuclear envelope. This is followed by a secondary envelopment in the cellular area surrounding the nucleus, called the cytoplasm (cytoplasmic envelopment).

Imaging methods that maintain the HSV-1-infected cells as close to physiological conditions as possible are needed to fully understand this complex, three-dimensional (3D) assembly process.

The authors used an emerging 3D imaging approach to study the envelopment mechanism and investigate the importance of different HSV-1 genes for viral assembly by investigating the impact of specific mutations of these viral genes. Their new approach combined two methods—cryo-structured illumination microscopy (cryoSIM) to detect fluorescently labeled capsid or envelope components, and cryo-soft-X-ray tomography (cryoSXT) to identify the cellular substructure in the same infected cells.

Together, this “correlative light X-ray tomography” (CLXT) approach makes it possible to identify specific structural components within the viral assembly process, allowing the team to visualize exactly where the assembly process stalls for each mutant virus, and providing insights into the unmutated gene’s usual role in viral assembly.

The authors captured different assembly stages during cytoplasmic envelopment using their mutant viruses and showed that—contrary to previous theories—cytoplasmic envelopment is caused by the budding of a capsid into an intracellular membrane “sack” or vesicle, and not by the capsid being “wrapped” by the vesicle membrane.

A further new finding is that this budding is asymmetric; the team observed several instances of stalled viral assembly where groups of capsids were gathered at one region, or side, of a spherical vesicle.

Using their CLXT approach, they were able to rank the relative importance of five of the mutant viral proteins in the process of nuclear egress. They were also able to reveal the role of a further five viral proteins in the cytoplasmic envelopment stage. For example, a protein called VP16 was found to be important in delivering the capsid to envelopment compartments and is now thought to have a larger role in nuclear egress than previously thought. In addition, the new method revealed that the absence of four other proteins caused virus particles to build up in the cytoplasm where assembly had stalled.

“Our multi-modal imaging strategy has provided novel ultrastructural insight into HSV-1 assembly, allowing the assembly trajectory of normal and mutant viruses to be observed in 3D,” concludes senior author Colin Crump, Professor of Molecular Virology at the University of Cambridge, U.K. “Our data underscore the power of correlative fluorescence and X-ray tomography cryo-imaging for interrogating and conducting further studies on the process of virus assembly.”

AI Model Measures Pace of Brain Aging, Could Aid Prediction of Cognitive Decline

Scientists at the University of Southern California (USC) have developed an artificial intelligence (AI) model that they say could help scientists better understand, prevent, and treat cognitive decline and dementia.

The first-of-its-kind three-dimensional convolutional neural network (3D-CNN) tool noninvasively analyses magnetic resonance imaging (MRI) scans from an individual patient to track brain changes with time and measure the pace—P—of brain aging.

Faster brain aging closely correlates with a higher risk of cognitive impairment, said Andrei Irimia, PhD, associate professor of gerontology, biomedical engineering, quantitative & computational biology, and neuroscience at the USC Leonard Davis School of Gerontology and visiting associate professor of psychological medicine at King’s College London. “This is a novel measurement that could change the way we track brain health both in the research lab and in the clinic. Knowing how fast one’s brain is aging can be powerful.”

Irimia is the senior author of the study, published in the Proceedings of the National Academy of Sciences, that describes the new model and its predictive power. In the team’s report, titled “Deep learning to quantify the pace of brain aging in relation to neurocognitive changes,” Irima and colleagues concluded, “This research complements existing strategies for AD risk assessment that estimate individuals’ rates of adverse cognitive change with age.”

Biological age (BA) is distinct from an individual’s chronological age (CA), Irimia said. Two people who are the same age based on their birthdate can have very different biological ages due to how well their body is functioning and how “old” the body’s tissues appear to be at a cellular level. “Mapping the pace P of brain aging can help to identify abnormal rates of neural aging that may reflect neurodegenerative disease risk,” the team stated. “Whereas neurodegenerative disease risk increases with chronological age (CA), biological aging varies across cells, tissues, organs, and individuals.”

Some common measures of biological age use blood samples to measure epigenetic aging and DNA methylation, which influences the roles of genes in the cell. However, measuring biological age from blood samples is a poor strategy for measuring the brain’s age.

The barrier between the brain and the bloodstream prevents blood cells from crossing into the brain, such that a blood sample from one’s arm does not directly reflect methylation and other aging-related processes in the brain Conversely, taking a sample directly from a patient’s brain is a much more invasive procedure, making it unfeasible to measure DNA methylation and other aspects of brain aging directly from living human brain cells. “Measuring P is challenging due to its dynamic nature throughout life,” the authors wrote. “The pace of aging is frequently estimated based on DNA methylation of whole-blood cells. However, this is not ideal for the brain because the blood–brain barrier separates neural cells from the blood physically and biochemically.”

Previous research by Irimia and colleagues highlighted the potential of MRI scans to non-invasively measure the biological age of the brain. The earlier model used AI analysis to compare a patient’s brain anatomy to data compiled from the MRI scans of thousands of people of various ages and cognitive health outcomes.

However, the cross-sectional nature of analyzing one MRI scan to estimate brain age had major limitations. While the previous model could, for instance, tell if a patient’s brain was ten years “older” than their calendar age, it couldn’t provide info on whether that additional aging occurred earlier or later in their life, nor could it indicate whether brain aging was speeding up.

Created in collaboration with Paul Bogdan, PhD, associate professor of electrical and computer engineering and holder of the Jack Munushian Early Career Chair at the USC Viterbi School of Engineering, the newly developed 3D-CNN offers a more precise way to measure how the brain ages over time, by analyzing MRI scans taken at different time points for the same patient. Unlike traditional cross-sectional approaches, which estimate brain age from one scan at a single time point, the new longitudinal model (LM) compares baseline and follow-up MRI scans from the same individual. As a result, it more accurately pinpoints neuroanatomic changes tied to accelerated or decelerated aging.

The authors first trained and validated the model on more than 3,000 MRI scans of cognitively normal (CN) adults. When applied to a group of 104 cognitively healthy adults and 140 Alzheimer’s disease patients, the new model’s calculations of brain aging speed closely correlated with changes in cognitive function tests given at both time points. The 3D-CNN also generates interpretable “saliency maps,” which indicate the specific brain regions that are most important for determining the pace of aging, Bogdan said. “The alignment of these measures with cognitive test results indicates that the framework may serve as an early biomarker of neurocognitive decline. “Moreover, it demonstrates its applicability in both cognitively normal individuals and those with cognitive impairment.”

Bogdan further commented that the model has the potential to better characterize both healthy aging and disease trajectories, and its predictive power could one day be applied to assessing which treatments would be more effective based on individual characteristics. “Estimated P values correlate significantly with changes in cognitive function, suggesting its utility for monitoring abnormal brain aging rates during neurodegeneration,” the scientists stated. “Rates of brain aging are correlated significantly with changes in cognitive function,” Irimia noted. “So, if you have a high rate of brain aging, you’re more likely to have a high rate of degradation in cognitive function, including memory, executive speed, executive function, and processing speed. It’s not only an anatomic measure; the changes we see in the anatomy are associated with changes we see in the cognition of these individuals.”

In their study, Irimia and coauthors noted how the new model was able to distinguish different rates of aging across various regions of the brain. Delving into these differences—including how they vary based on genetics, environment, and lifestyle factors—could provide insight into how different pathologies develop in the brain, Irimia said.

The study also demonstrated that the pace of brain aging in certain regions differed between the sexes, which might shed light on why men and women face different risks for neurodegenerative disorders, including Alzheimer’s, he added. “By synergizing the LM with an interpretable CNN saliency approach, we map anatomic variations in regional brain aging rates that differ according to sex, decade of life, and neurocognitive status,” the investigators stated. “LM estimates of P are significantly associated with changes in cognitive functioning across domains. This underscores the LM’s ability to estimate P in a way that captures the relationship between neuroanatomic and neurocognitive aging.”

Irimia said he is also excited about the potential for the new model to identify people with faster-than-normal brain aging before they show any symptoms of cognitive impairment. While new drugs targeting Alzheimer’s have been introduced, their efficacy has been less than researchers and doctors have hoped for, potentially because patients might not be starting the drug until there is already a great deal of Alzheimer’s pathology present in the brain, he explained. “Individually tailored strategies to reduce P could increase healthspan and maintain functions that diminish with age,” the team concluded.

“One thing that my lab is very interested in is estimating risk for Alzheimer’s; we’d like to one day be able to say, ‘Right now, it looks like this person has a 30% risk for Alzheimer’s,’” Irima said. “We’re not there yet, but we’re working on it. I think this kind of measure will be very helpful to produce variables that are prognostic and can help to forecast Alzheimer’s risk. That would be really powerful, especially as we start developing potential drugs for prevention.”

Study Shows Anti-Aging Potential for Insilico’s IPF Candidate

Researchers from artificial intelligence (AI) drug developer Insilico Medicine and two partner institutions have published a study concluding that its lead candidate ISM001-055 is the first to show anti-aging properties and that its mechanism of action offers a promising therapeutic approach for treating age-related diseases.

ISM001-055 was shown to have attenuated cellular senescence through the suppression of various aging processes, thus showing potential as a senomorphic drug. Senomorphics are a class of drugs that targets the senescence-associated secretory phenotype (SASP) of senescent cells, which have stopped dividing and accumulate in tissues as people age, thus are considered to play a role in aging and age-related diseases.

The study also showed ISM001-055 to function as a senomorphic agent, modulating the behavior of senescent cells rather than eliminating them. ‘055 not only matched, but also surpassed the FDA-approved sirolimus, formerly rapamycin—sold by Pfizer as Rapamune® and by several other companies as generic versions—in two key areas:

  • Reduction of SASP factors: ISM001-055 was more effective than rapamycin in decreasing the secretion of pro-inflammatory cytokines and other SASP components, which are linked to tissue dysfunction and age-related pathologies.
    • Restoration of cellular function: Cells treated with ISM001-055 exhibited a more pronounced return to youthful functionality compared to those treated with rapamycin, indicating superior rejuvenative properties.

    ISM001-055 is an internally developed Insilico drug candidate developed using generative AI. The drug is designed to treat idiopathic pulmonary fibrosis (IPF) by targeting Traf2- and NCK-interacting kinase (TNIK), a serine/threonine kinase whose activation plays a crucial role in cellular processes that include signal transduction pathways essential for fibrosis development.

    In inhibiting TNIK, ISM001-055 reduced the activation of the TGF-β and Wnt/β-catenin pathways, which are involved in SASP regulation. This enabled ‘055 to suppress pro-inflammatory cytokine production while preserving senescent cells that may still serve beneficial functions, such as in tissue repair and tumor suppression.

    “The strong evidence that TNIK plays a role in aging and senescence could influence Insilico to expand the development of ISM001-055 beyond fibrosis and into broader geroprotective and anti-aging applications,” Insilico founder and CEO Alex Zhavoronkov, PhD, told GEN Edge.

    Insilico’s future plans for INSM001-055 are undisclosed.

    Implicating TNIK in aging

    “This study further strengthens the potential of INS018_055 as a longevity therapeutic by implicating TNIK in the cellular senescence hallmark of aging,” the researchers concluded, using the drug candidate’s former name, in “AI-Driven Robotics Laboratory Identifies Pharmacological TNIK Inhibition as a Potent Senomorphic Agent,” a study published in Aging and Disease. The Insilico researchers were joined by investigators from China’s Suzhou Hospital of Nanjing Medical University, as well as from the Buck Institute for Research on Aging.

    “This research highlights the novel role of TNIK in cellular senescence and new senomorphic applications for INS018_055, in addition to its anti-fibrotic properties that may inform future efforts to treat age-related diseases,” the researchers added.

    ISM001-055 has generated positive results in a “Phase 0” microdose trial (ACTRN12621001541897) and two Phase I clinical trials, one conducted in New Zealand (NCT05154240) and the other, in China (CTR20221542)—as well as a Phase IIa trial conducted across 21 sites in China (NCT05938920). That study’s secondary efficacy endpoint showed dose-dependent improvements in forced vital capacity (FVC), with the largest improvement observed in the 60 mg QD [once daily] cohort.

    Insilico is working to validate findings from these studies through a parallel Phase IIa trial (NCT05975983) now enrolling patients in the United States. The study is projected to enroll a total of 60 patients and achieve primary completion in February 2026.

    However, the results detailed in the latest paper came not from these clinical trials but from a study Insilico carried out at its AI-based, sixth-generation robotics laboratory in Suzhou, China, which according to the company, allowed for increased validation and consistency across experiments.

    “Insilico conducted this separate study using its AI-driven robotics lab to explore the senomorphic potential of ISM001-055 beyond its known anti-fibrotic effects,” Zhavoronkov said. “The robotic study provides high-throughput, automated, and AI-driven analysis of cellular responses, allowing for a detailed mechanistic understanding of how ISM001-055 impacts cellular senescence. This approach enables the identification of molecular pathways, aging biomarkers, and transcriptional changes in response to treatment.”

    Reducing inflammatory cytokines

    Researchers found that ISM001-055 primarily attenuates SASP by reducing inflammatory cytokines such as IL-6, IL-8, IL-1A, and IL-1B. ‘055 also attenuates extracellular matrix (ECM) remodeling, preventing excessive fibrosis and tissue dysfunction; as well as TGF-β signaling, a major driver of fibrosis and senescence-associated inflammation.

    In addition to reducing inflammation, results of attenuation included improving mitochondrial function, and outright increasing of healthy years or “healthspan.”

    Which effects is Insilico most interested in seeing?

    “Improving mitochondrial function and increasing healthspan are incredibly important and a major goal,” Zhavoronkov explained. “The most immediate translational impact comes from mitigating chronic inflammation and ECM remodeling, which are major drivers of aging-related diseases.”

    Zhavoronkov added that Insilico will continue focusing on reducing inflammation and SASP, since they contribute directly to multiple age-related diseases, including fibrosis and chronic inflammatory conditions.

    “Insilico will continue to confirm the findings by conducting more validating studies to ensure that the senomorphic effects observed in cellular models translate into whole-organism benefits. As progress continues, additional trials targeting aging-related diseases and conditions driven by senescence may be launched,” Zhavoronkov said.

    The researchers acknowledged they will need to collect additional data to support ISM001-055’s use for anti-aging therapy in clinical settings. According to Zhavoronkov, potential ways to further collect this data may include:

    • Animal model studies intended to validate ‘055’s effects on senescence and aging in vivo
    • Biomarker studies designed to identify changes in aging-related molecular markers in treated organisms
    • Potential expansion of clinical trials to evaluate its effects on age-related diseases beyond IPF
    • AI-driven modeling to refine target selection and optimize dosing strategies for anti-aging effects

    In a paper published in March in Nature Biotechnology, a team of 30 researchers led by Zhavoronkov detailed how they used generative AI to discover INS018_055, with a novel target discovered by Insilico’s target identification engine, PandaOmics, and a novel molecular structure designed by its generative chemistry engine, Chemistry42. Both are specific-function platforms within the company’s AI platform, Pharma.AI.

    ISM001-055 is Insilico’s first wholly owned program in which AI was used to identify a novel target and generate novel small molecules through Pharma.AI. Insilico won the FDA’s first Orphan Drug Designation for an AI drug in 2023.

MD Anderson Receives Nearly $23 Million for Cancer Research and Faculty Recruitment

The Cancer Prevention and Research Institute of Texas (CPRIT) awarded the University of Texas MD Anderson Cancer Center nearly $23 million in support of 20 cancer research projects to advance new breakthroughs in discovery, translational, clinical, and prevention science. In addition, CPRIT awarded $2 million for the recruitment of one first-time, tenure-track faculty member.

“We sincerely appreciate CPRIT’s continued funding of impactful cancer research that will help us achieve our mission to end cancer,” said Giulio Draetta, MD, PhD, CSO, MD Anderson. “This critical support allows our world-class scientists and clinicians to enhance our understanding of cancer biology and to develop strategies to better prevent, diagnose, and treat the disease, improving the lives of patients and their families.”

Grants for $3.7 billion for cancer research

Since its inception, CPRIT has awarded over $3.7 billion in grants for cancer research. MD Anderson investigators have received more than $675 million all told, approximately 18% of the total awards. Programs supported by CPRIT funding have brought more than 324 distinguished cancer researchers to Texas, advanced the knowledge base for cancer treatment throughout the state, and provided more than 10.1 million cancer prevention and early detection services reaching all 254 counties in Texas.

Academic research awards to MD Anderson include:

  • Leveraging synthetic and collateral lethality in MTAP loss tumors (Jordi Rodon Ahnert, MD, PhD, Investigational Cancer Therapeutics)— $1,599,783
  • Randomized clinical trial evaluating fecal microbiota transplant in chimeric antigen receptor therapy for reversing antimicrobial-associated dysbiosis (Neeraj Saini, MD, Stem Cell Transplantation and Cellular Therapy)—$1,598,410
  • Serum cell-free DNA methylation and radiomics signatures for the early detection of recurrence after initial treatment in HPV-associated oropharyngeal cancer (Jia Wu, PhD, Imaging Physics)—$1,200,000
  • Cancer-related fatigue and its biological contributors in adolescent and young adult brain tumor survivors: Effects of a tele-exercise intervention (Maria Swartz, PhD, Pediatrics)— $1,199,756
  • Development of a shared decision tool to facilitate uptake of the levonorgestrel-releasing intrauterine system for the primary prevention of endometrial cancer (Larissa Meyer, MD, Gynecologic Oncology and Reproductive Medicine)—$1,199,542
  • Blood-based biomarkers to guide clinical decision-making with indeterminate pulmonary nodules (Edwin Ostrin, MD, PhD, General Internal Medicine)—$1,169,776
  • Dissecting mechanisms of resistance to immune checkpoint blockade in non-small cell lung cancer (NSCLC) through the interplay of molecular and spatial architecture (Natalie Vokes, MD, Thoracic–Head & Neck Medical Oncology)—$1,049,033
  • MALAT1 protects against osteoporosis and bone metastasis (Li Ma, PhD, Experimental Radiation Oncology)—$900,000
  • Mechanisms of resistance to tyrosine kinase inhibitors (TKIs) and antibody-drug conjugates (ADCs) in HER2-mutant NSCLC (John Heymach, MD, PhD, Thoracic–Head & Neck Medical Oncology)—$900,000
  • Innovative in vitro and in vivo patient-derived cancer models to advance precision medicine in G1/G2 GEP-NETs (James Yao, MD, Gastrointestinal Medical Oncology)— $900,000
  • Neoadjuvant combination anti-PD-L1 and anti-TIGIT immune checkpoint blockade in oral cavity squamous cell carcinoma (Maura Gillison, MD, PhD, Thoracic–Head & Neck Medical Oncology)—$899,998
  • KRAS inhibitor-induced adaptive resistance mechanisms and immune suppression in NSCLC (Don Gibbons, MD, PhD, Thoracic–Head & Neck Medical Oncology)—$899,997
  • Synthetic lethality of TRIP13 and Aurora A in Rb-deficient cancer (Faye Johnson, MD, PhD, Thoracic–Head & Neck Medical Oncology)—$899,994
  • Understanding and overcoming resistance of SMARCA4-mutant lung cancers to immunotherapy (Yonathan Lissanu, MD, PhD, Thoracic and Cardiovascular Surgery)— $899,991
  • Deciphering and targeting age-related metastatic competence of the omentum (Honami Naora, PhD, Molecular and Cellular Oncology)—$899,984
  • Clonal hematopoiesis and toxicity from radiation therapy (Kevin Nead, MD, Epidemiology)—$899,885
  • Improving detection of hepatocellular carcinoma in non-cirrhotic metabolic dysfunction associated steatohepatitis (MASLD) patients (David Fuentes, PhD, Imaging Physics)—$899,808
  • Engineering second-generation in vivo chimeric antigen receptor macrophages (CARMs) for glioblastoma therapy (Wen Jiang, MD, PhD, Radiation Oncology)—$898,263
  • Exploiting synthetic lethalities between HNRNPK loss and ribosomal dysfunction in del9q AML (Sean Post, PhD, Leukemia)—$896,322
  • HSP90 capacitance: Discovery of a new mechanism driving evolution of drug resistance in head and neck squamous cell carcinoma (Georgios Karras, PhD, Genetics)—$890,201
Atrandi Raises $25M to Develop New Products Based on Semi-Permeable Capsule Tech

Atrandi Biosciences has raised $25 million in a Series A funding round led by Lux Capital, with participation from Vsquared Ventures, Practica Capital, Metaplanet, and CRIDS Capital. The company plans to use the funds to develop new products based on its semi-permeable capsule (SPC) technology as well as to set up an office in Boston which will allow the company to better serve its U.S. customer base.

Atrandi, which means “you discover” in Lithuanian, was launched in 2016 to address technological challenges associated with single-cell analysis. As Juozas Nainys, PhD, Atrandi’s CEO & co-founder, explained, the company was launched “to bridge a fundamental gap in biological research—the need for high-throughput, scalable technologies to manipulate and analyze single cells with precision.” Furthermore, “our SPC technology is a fundamental breakthrough born from a need to overcome the limitations of existing single-cell analysis tools, giving researchers the possibility to generate rich datasets with an unprecedented combination of throughput, multimodality and data quality.”

Atrandi will use some of the funds from its Series A to extend its offerings for DNA analysis from single cells, Nainys told GEN. The company already has a solution for microbial cells and expects to launch an option that works for eukaryotic cells later this year. They will be able to support whole genome analysis as well as more targeted analysis of single cells. Next year, Atrandi will focus on developing products for multi-omic analysis—specifically DNA and RNA analysis from single cells.

Designed for high-throughput single-cell research, Atrandi’s SPCs are aqueous compartments that are enclosed by a semi-permeable shell. They are designed to isolate single cells and nucleic acids while enabling the exchange of small molecules like enzymes and nutrients. The ability to exchange materials is an important part of SPCs value proposition for single cells and something that sets Atrandi’s technology apart from current droplet microfluidics technologies, according to Nainys. Typically, “once you form a droplet you can add reagents to it … but you can never remove [them],” he explained. “That’s very limiting [because] there are so many different molecular biology reactions that just do not work together or require specific pH [and] buffers.”

Nainys interest in single-cell technologies predates Atrandi’s founding. During his PhD, he worked in a laboratory focused on developing single-cell RNA sequencing technologies. “The single-cell revolution was really brought about by droplet microfluidics,” he said. “The lab that I joined specialized in droplet microfluidics and as experts in that particular technology, we saw that there are … a lot of things that can not be done in droplets.” That led him and Atrandi’s co-founders to launch the company in 2016 with an eye toward developing and commercializing SPCs as well as instruments for generating them.
The two other products in Atrandi’s portfolio are the Onyx Droplet Generator, a microfluidic platform designed for high-throughput single-cell and single-molecule applications, and the Styx High-Throughput Screening Platform, which is designed for fluorescence-activated droplet sorting. These platforms are designed for users who want more control of their workflows and the ability to adjust different parameters as needed, Nainys said. They are compatible with SPCs as well as droplets. Additionally, “we also worked hard to make sure that the capsules integrate well with any readout method” including sequencing instruments, microscopy, and mass spectrometers.
So far, Atrandi has installed over 150 devices in labs in Europe, North America, and South Korea where they are used for a wide range of applications. About half of its customers are based in U.S. laboratories. People are using the solutions in different ways including studies in oncology, immunology, and microbiology, Nainys said. “It really is all over the map but at the end of the day it’s analyzing single cells as part of a complex biological system.” 
Arc Institute’s AI Model Evo 2 Designs the Genetic Code Across All Domains of Life

“Today, we can for all practical purposes read, write, and edit any sequence of DNA, but we cannot compose it. Maybe we can cut and paste pieces from nature’s compositions, but we don’t know how to write the bars for a single enzymatic passage. However, evolution does.” —Frances Arnold, PhD (Nobel Prize Lecture 2018)

Evo, the genome foundation model developed by the Arc Institute published last November that generalizes across the languages of biology — DNA, RNA, and proteins for both predictive and generative capabilities — has received a major update.

In a new preprint that is not yet peer-reviewed and first published on Arc’s website, Evo 2 moves beyond single-cell genomes of bacteria and archaea to include information from humans, plants, and other more complex single-celled and multi-cellular species in the eukaryotic domain of life.

The model’s resulting research applications span a diverse array of scientific fields including drug discovery, agriculture, industrial biotechnology, and material science. The multimodal and multiscale work is a collaboration with Nvidia along with contributors from Stanford University, UC Berkeley, and UC San Francisco.

“The recipe for life is entirely present in the genetic information contained in our DNA,” said Kimberly Powell, vice president of healthcare at Nvidia. “We’re seeking a deeper understanding of biological complexity. Evolution has solved this problem over millions of years, and Evo 2 aims to learn from this knowledge.”

In healthcare, understanding which gene variants are tied to a disease is an invaluable tool for therapeutics. Early validation of Evo 2’s capabilities showed that the model can identify how genetic mutations affect protein, RNA, and organismal fitness. In tests with variants of BRCA1, a gene associated with breast and ovarian cancer risk, Evo 2 achieved greater than 90% accuracy in predicting which mutations are benign versus disease-causing.

Patrick Hsu, PhD, Arc Institute co-founder and an assistant professor of bioengineering at UC Berkeley, stated that Evo 2 is the only model that can predict the effects of both coding and noncoding mutations.

“It is the second-best model for coding mutations, but it is state-of-the-art for noncoding mutations, which other variant effect prediction methods, such as AlphaMissense from DeepMind, cannot score,” said Hsu.

Hsu also described Evo 1 as a “blurry picture of single-cell life” because it was trained on a corpus of 300 billion nucleotides derived from prokaryotic genomes. The team “wanted to be much more ambitious” in this collaboration with Nvidia.

Evo 2 was built on NVIDIA’s DGX Cloud platform and is trained on more than 9.3 trillion nucleotides from the genomes of more than 128,000 species across the tree of life. The model uses a novel architecture called StripedHyena 2, which enabled training that was “nearly three times faster than optimized transformer models,” according to Dave Burke, PhD, chief technology officer at Arc Institute. The model also has 40 billion parameters and is similar in scale to the current generation of large language models released from Meta, DeepMind, or OpenAI.

Evo 2 can process DNA sequences of up to 1 million nucleotides at once, allowing it to understand relationships between distant parts of the genome. Hsu stated that this long context length unlocks multiple molecular scales, from short biological molecules, such as tRNA, or clusters of genes (e.g., operons), to entire bacterial genomes or eukaryotic chromosomes.

Arc Institute and Nvidia describe Evo 2 as the “largest publicly available AI model for biology to date.” Evo 2 is available for public use on the NVIDIA BioNeMo platform and as an interactive user-friendly interface called Evo Designer. In addition, the authors have made its training data, training and inference code, and model weights open source.

Biology’s app store 

Understanding biology as a “language” is not a new concept. Advances in genome sequencing have allowed us to “read” the human genome, while the invention of CRISPR technology expanded our toolbox to gene “editing.”  

In 2023, Hsu and Brian Hie, PhD, assistant professor of chemical engineering at Stanford University, began thinking about designing or “writing” biological sequences, including proteins, by starting at the foundational layer of DNA itself. “After all, proteins themselves are encoded directly by the genome,” emphasized Hsu.  

“Machine learning started to revolutionize biology, and models such as AlphaFold or ESMFold enabled protein structure prediction and design. Despite these advances, the complexity of these molecules is dwarfed by the overall complexity of an entire cell,” Hsu continued. 

Given that biological functions are not accomplished by a single protein molecule in isolation, constructing synthetic genomes can provide a valuable research tool to investigate broader biological context, a feat that Evo 2 is tackling head-on. 

“A lot of biological design until now has focused on the molecular level because that’s all that we could control. If we have a powerful model that lets us generate at the scale of complete organisms, then that unlocks a lot of downstream tasks [with a wide array of use cases],” said Hie. 

The Evo 2 preprint described three design tasks that span different levels of genomic complexity: 1) mitochondrial genome 2) prokaryotic genome of Mycoplasma genitalium, a commonly used model of the minimum genome, and 3) yeast chromosome, which represents eukaryotic organisms.

For all three design tasks, the preprint showed evidence supporting genome coherence, such as the construction of genes that code for all the components of the electron transport chain (as predicted by AlphaFold 3) in the case of the mitochondrial genome, and the presence of natural homologs and more complex genomic architecture, such as introns, in the case of the yeast chromosome. 

The preprint also presented a workflow for “generative epigenomics,” which designed DNA sequences with desirable chromatin accessibility profiles to simulate eukaryotic gene regulation.  

When asked about plans for experimental validation, Hie stated that a collaboration with large DNA synthesis and assembly experts from the University of Washington is underway to insert the chromatin accessibility designs into mouse cells for validation studies. 

Looking ahead, the Arc Institute is interested in building on this biological complexity by constructing the virtual cell.  

“The bottleneck to drug discovery is that we don’t know what causes the disease to begin with,” said Hie. “If we have a very capable model of the genome and we couple this with information from the environment through RNA sequencing, gene regulatory networks, and cell signaling networks, then this combined multimodal framework will let us answer these fundamental questions about disease.”

Hie sees Evo 2 as an “operating system”, or a foundational layer, that provides a platform for broad generative functional genomics. While Evo 2 “might not solve all questions in biology,” the model offers a wider breadth of applicability compared to task-specific predecessors, such as AlphaFold for protein structure prediction. 

“We want to empower the research community to build on top of these foundation models. That’s why we put in so much effort with Nvidia to make this fully open source,” weighed in Hsu. “We’re really looking forward to how scientists and engineers build on this ‘app store’ for biology.” 

Genome-edited rice shows resistance to bacterial blight in East Africa

The international Healthy Crops consortium has developed an innovative strategy to combat the disease bacterial blight (for short: BB) in rice using genome editing technology. If approved for use by farmers in Kenya, the BB-resistant rice varieties are expected to reduce yield losses associated with the disease in the affected rice growing regions and increase productivity. The work is a collaboration between Kenya Agricultural and Livestock Research Organization (KALRO) and Heinrich Heine University Düsseldorf (HHU).

Rice production is of central importance for food security and economic development in many countries, in particular in low- and medium-income countries. Rice is the second most important staple food in East Africa, with 1.8 million tonnes consumed every year in the countries of the East African Community (for short: EAC).

In 2019, members of the Healthy Crops team identified an outbreak of BB in Tanzania caused by invasive Asian variants of the bacterium Xanthomonas oryzae pv. oryzae (Xoo). The bacterium is spreading rapidly and causing estimated yield losses of 13–20%.

Dr. Emily Gichuhi from KALRO explains, “Due to climate change, incidences of rice diseases including BB have been on the rise in Kenyan rice growing areas. This has increased the cost of production among rice farmers, thereby reducing their returns.”

Dr. Daigo Makihara and Dr. Moto Ashikari from Nagoya University (NU) in Japan, researchers from the Wonder Rice Initiative for Food Security and Health (WISH), are working closely with Dr. Gichuhi and her team to develop new African rice varieties. Dr. Makihara explains, “As a result of the international spread of different crop plant varieties, we are increasingly finding ourselves confronted with outbreaks of plant diseases in regions where they have not previously played a role.”

The starting point for the researchers from Healthy Crops is the nutrient supply of the bacteria. The Xoo bacteria possess a set of “keys” which can open the “pantry” of the plants: When the bacterium injects one of these “key” proteins into rice cells, it leads to increased production of a transporter, which releases sugar in the neighborhood of the bacteria. This sugar serves as nutrition and is essential for the multiplication and virulence of the bacteria. However, when the bacteria utilize the sugar, there is none left for the plant, which ultimately dies as a result.

The research team has succeeded in changing the “locks” via genome editing, making the plants resistant to all known Xoo strains currently prevalent in Asia and Africa.

Professor Bing Yang, University of Missouri, who developed the editing approach, states: “The combination of two different sets of enzymes for editing enabled us to develop a robust resistance.”

The import of these edited elite rice varieties has been made possible due to the availability of genome editing guidelines developed by the National Biosafety Authority (NBA) of Kenya and published in 2022.

Dr. Marcel Buchholzer, coordinator of the Healthy Crops project at HHU, explains, “It is now possible to evaluate these rice lines, developed using advanced biotechnology methods at HHU, in Kenya.”

Professor Dr. Wolf B. Frommer, spokesperson for the project at HHU explains, “This project aims to protect smallholder farmers from crop yield losses through knowledge-based approaches to fighting plant diseases.”

Unraveling structure and function relationships in synthetic cell receptors

Northwestern University researchers have identified structural features in engineered cell receptors that correlate with variations in receptor function.

Computational protein structure prediction tools were used to analyze a library of synthetic receptors, revealing that specific structural attributes such as ectodomain (ECD) distance and transmembrane domain (TMD) interactions are associated with receptor performance.

Engineered cell therapies rely on synthetic receptors to transduce external signals into intracellular responses. The precise relationship between receptor structure and function remains poorly understood. Advances in protein structure prediction tools, such as AlphaFold and ColabFold, have enabled the modeling of complex proteins, including single-pass transmembrane receptors.

In the study, “Exploring Structure-Function Relationships in Engineered Receptor Performance Using Computational Structure Prediction,” published in GEN Biotechnology, researchers integrated predicted protein conformations with experimental performance metrics across four engineered receptor families, examining whether certain molecular features correlated with functional output.

Researchers analyzed a library of engineered receptors derived from natural cytokine receptors, focusing on Modular Extracellular Sensor Architecture (MESA) receptors. MESA receptors use ligand-induced dimerization to activate a split Tobacco Etch Virus Protease (TEVp), which releases a transcription factor to drive gene expression.

ColabFold was used to generate structural models of receptor ECDs in complex with their ligands, while PREDDIMER was employed to model TMD interactions.

Structural features were quantified, including ECD distance, ECD contacts, TMD distance, TMD contacts, TMD crossing angle, and TMD exit angle. Receptor performance was assessed based on on-state reporter expression (OS) and fold induction (FI) in experimental data.

Substantial variation in receptor performance was explained by structural features. Shorter ECD and TMD distances correlated with higher OS, while greater ECD and TMD contacts were also associated with improved performance. TMD exit angle had a significant relationship with receptor function in certain receptor families, particularly in tumor necrosis factor (TNF) MESA.

Structural models explain less variation in performance for heterotetrameric receptors, such as interleukin-10 (IL-10) MESA and transforming growth factor beta (TGFb) MESA. This suggests that additional factors, such as higher-order receptor complex formation, may contribute more to the performance of these receptors.

To complement structural analyses, the researchers evaluated categorical variables representing domain choices within receptor chains. One-hot encoding of receptor components revealed that VEGF MESA receptors containing a CD28 TMD in the C-terminal chain and a VEGFR1 ECD exhibited higher OS. The reduced categorical model explained 57% of OS variation, closely aligning with the structural model’s performance.

A combined model integrating both structural and categorical features demonstrated superior predictive power, explaining 79% of OS variation. This improvement indicates that while structural and categorical models share some information, they capture distinct determinants of receptor performance.

The findings present actionable hypotheses for synthetic receptor engineering. For instance, modifying receptor linkers to enhance ECD contacts or selecting TMD pairs that favor closer C-terminal proximities could improve receptor function.

A notable challenge in this work was modeling the entire single-pass transmembrane receptor,including the natural ectodomain (ECD), the transmembrane domain (TMD), and the split TEVp intracellular domains (NTEVp or CTEVp) using ColabFold.

Specifically, the tool struggled with aligning the shorter TEVp regions within long receptor sequences. During the multiple sequence alignment (MSA) search step, the sizable ECD and native TMD often dominated the alignment results, causing ColabFold to drop or poorly cover the TEVp segments.

As a result, the predicted structures sometimes failed to show a properly folded NTEVp or CTEVp, yielding low-confidence scores (pLDDT) in those intracellular portions.

Shorter ectodomains (e.g., IL-10 receptors) were more likely to retain coverage for the TEVp domains, allowing a few full-length models to converge on structures where the NTEVp and CTEVp were reconstituted.

Because of these alignment issues, the study opted for a modular approach, modeling ECD–ligand complexes separately with ColabFold and then using PREDDIMER to capture TMD–TMD interactions.

While this strategy prevented direct visualization of how NTEVp and CTEVp might orient themselves under membrane constraints, it ensured higher confidence in the predicted extracellular and transmembrane regions. The trade-off is that intermolecular effects were not fully captured.

HBV’s Ability to Infect Human Liver Cells Thwarted by Potential Anticancer Drug

As part of their effort to answer a decades-old biological question about how the hepatitis B virus (HBV) can establish an infection in liver cells, researchers led by teams at Memorial Sloan Kettering Cancer Center (MSK), Weill Cornell Medicine, and the Rockefeller University have identified a vulnerability that may open the door to new HBV treatments.

The team successfully disrupted the virus’s ability to infect human liver cells in the laboratory using a chromatin-destabilizing molecule CBL137, which is already in clinical trials against cancer. The results lay the groundwork for animal model studies and potential drug development.

Headed by chemical biologist Yael David, PhD, at MSK, working with hepatologist and virologist Robert Schwartz, MD, PhD, at Weill Cornell Medicine and Viviana Risca, PhD, at the Rockefeller University, the researchers reported on their findings in Cell, in a paper titled, “A nucleosome switch primes hepatitis B virus infection.”

Chronic HBV infection is an incurable pathogen responsible for causing liver disease and hepatocellular carcinoma, the authors wrote. “Over 325 million people worldwide are chronically infected by hepatitis B virus … leading to almost one million deaths annually despite the availability of effective vaccines.” Chronic infection leaves patients at risk for advanced liver disease, and HBV is estimated to cause nearly half of all hepatocellular carcinoma cases, the team continued.

The newly reported research began with a chance meeting and a longstanding paradox. Schwartz, an associate professor of medicine in the Division of Gastroenterology and Hepatology at Weill Cornell Medicine, was introduced to David about six years ago at a retreat for Weill Cornell Physiology, Biophysics, and Systems Biology graduate school faculty, where they both hold appointments.

“On the surface, our research programs seem to have no overlap,” David said. “He studies hepatitis B, while my lab focuses on understanding how gene expression is regulated through a process called epigenetics. However, I was fascinated to discover that viruses like hepatitis B hijack epigenetic mechanisms, even using human DNA-packaging proteins to regulate their activity.”

Not long after, study first author Nicholas Prescott, PhD, then a doctoral student in the Tri-Institutional PhD Program in Chemical Biology, was preparing for a stint in the David Lab at MSK’s Sloan Kettering Institute. “His interest in epigenetic regulation in pathogens immediately made me consider HBV an ideal model system for him to explore,” David said.

At the heart of the mystery that intrigued the researchers lies a key viral gene that encodes for the HBV X protein (HBx). This protein is essential for HBV to establish a productive infection in host cells and the expression of its viral genes. However, the X gene itself is encoded within the viral genome.

“This raises a classic chicken-and-egg question that has puzzled scientists for decades,” David said. “How does the virus produce enough X protein to drive viral gene expression and establish infection?” The authors further commented “… HBx is absent from the virion and must be expressed de novo in freshly infected hepatocytes …”

Furthermore, the gene that encodes protein X is considered the virus’s oncogene—that is, the gene responsible for the disease’s progression toward cancer, Prescott added. That’s because protein X degrades proteins in the host that are involved with DNA repair. Not only does this keep the host from silencing protein X’s activity, but the infected cells are also more likely to accumulate DNA errors that build up over the years and decades, leading to the development of cancer.

“One of the main challenges with treating hepatitis B is that the existing treatments can stop the virus from making new copies of itself, but they don’t fully clear the virus from infected cells, allowing the virus to persist in the liver and maintain chronic infection,” noted Schwartz, whose lab contributed biological and clinical expertise in the virus, as well as the human liver cell models used in the study. “The current standard of care (long-term treatment with oral nucleos(t)ide analogs or short-term treatment with interferon-alpha injections) halts viral replication but falls short of eradicating cccDNA in infected hepatocytes, allowing the minichromosome to persist and sustain chronic infection,” the investigators stated. “Even with long-term antiviral treatment, basal levels of the HBV oncogenic X protein (HBx) remain in hepatocytes to promote genomic instability and disease progression.”

The hepatitis B vaccine is effective, but maintaining immunity often requires booster shots. Moreover, it doesn’t help people who are already infected. This happens, for example, due to transmission of the virus from mother to child, which is very common in developing countries. Access to vaccines and treatment is also more limited in some parts of Africa and Asia, where rates of infection are higher.

Digging into the mystery of protein X was a challenge, explained Prescott, who is now a postdoctoral fellow in the Laboratory of Chromosome and Cell Biology at the Rockefeller University. The existing tools weren’t capable of shedding light on what was happening in those critical early hours of an infection.

Early in infection, HBV establishes an independent “minichromosome” consisting of the viral covalently closed circular DNA (cccDNA) genome and host histones. But as the authors noted, “Despite extensive study, a significant knowledge gap remains regarding the role of viral chromatin status in establishing infection.”

The David Lab’s expertise is in how DNA gets packaged, read, and modified proved essential. For their newly reported research, the researchers successfully generated the HBV minichromosome for the first time, using their capabilities in reconstituting viral DNA in complex with human histones—the proteins that package and organize DNA. The research team determined that in order for protein X to get made, the hepatitis B virus’s DNA needs to get organized into DNA-histone complexes called nucleosomes. “… we generated recombinant, chromatinized cccDNA, allowing us to characterize its biophysical properties and to map nucleosome positioning on the minichromosome,” the scientists explained.

“This platform became a powerful tool not only to study the virus’s biochemistry but also to analyze, in detail, what happens in the critical first hours of an infection,” David said.

Nucleosomes are like beads on a string—the string is the viral DNA, and the beads are host-provided histone proteins, around which DNA gets wrapped; nucleosomes are the building blocks of chromatin, the material that makes up chromosomes.

It was this part of the project that tapped into the expertise of Risca at Rockefeller University. The Risca Lab studies the 3D architecture of the genome and how the packaging of DNA helps to control the transcription of genes. They had the tools and expertise to ensure that what the scientists were seeing in the new platform for studying the virus matched the reality of a human infection.

“Conventional wisdom says that packaging a gene’s DNA into nucleosomes would block or slow down the cell’s ability to read out that gene to make functional proteins, like protein X,” Risca commented. “But in complex organisms like humans and in the viruses that infect us, gene regulation is not always so straightforward. The presence and the positioning of nucleosomes on DNA can be important in directing cellular mechanisms to transcribe some genes. We found that to be the case for the HBV gene encoding protein X—the presence of nucleosomes on the viral genome is necessary for the transcription of RNA that gives rise to functional protein X.” The authors added. “Altogether, these data suggest a correlation between early cccDNA chromatinization and X transcription, which both occur during the first hours of infection.”

This discovery opens the door to understanding how the X gene is regulated and how HBV infection is established. Moreover, the researchers discovered a potential therapeutic opportunity. If it’s possible to disrupt the formation of these chromatin structures, then this could disrupt the virus’s ability to start and maintain an infection. “Given this link between chromatinization and transcription, we next hypothesized that disrupting chromatin assembly might inhibit viral transcription,” they wrote.

The team tested five small-molecule compounds known to impair chromatin formation. Only one, an anticancer drug candidate called CBL137, blocked production of protein X in liver cells.

Importantly, the compound worked in vitro at very low concentrations—many times smaller than participants in clinical trials for cancer were receiving, and using doses that only affected the virus, but not human cells. Their experimental results, they noted, “… demonstrate CBL137 as an effective inhibitor of HBV transcription and replication that may pose a potential therapeutic avenue to treat infections.”

David noted, “This made us very optimistic about the possibility of developing a treatment approach while preventing or limiting side effects. Moreover, if these results are confirmed through additional study, we are optimistic the approach could be used to treat chronic infections for the first time—and therefore could represent a potential cure.”

Additionally, CBL137 might prove similarly useful to target or study other chromatinized DNA viruses such as herpesviruses and papillomaviruses, the researchers noted. “Chromatin destabilization by CBL137 merits further investigation to test if it could prove similarly effective on other pathogens. Indeed, recent studies reported encouraging results for CBL137 as a latency reversing agent in HIV-1 infection and even a lead for drug discovery efforts against human African trypanosomiasis, underscoring its potential as a therapeutic against infectious diseases.

The project David pointed out, “…started from our fundamental interest in how the virus’s chromosomes might look and function and led to unexpected discoveries of how the viral infection is established in human cells.”

To further develop the team’s research toward a potential clinical trial, the next step would be to study the safety and effectiveness of CBL137 in animal models—though these are limited due to the narrow range of species HBV can infect, the researchers said.

All of the researchers stressed that the study wouldn’t have been possible without the close collaboration between the three institutions, which brought together the necessary expertise and technological resources—from MSK’s atomic force microscope to the Genomics Resource Center and High-Performance Computing Cluster at Rockefeller University.

Prescott commented, “This is a great example of how investment in ‘basic science’ and investigation of fundamental biological questions can open the door to medical advances,” he said. “I always thought I’d be working on questions that decades later someone might cite in a paper when they come up with a cure for some disease. Never in a million years did I expect to lead a project that identified such a strong candidate for drug development for a global scourge like hepatitis B.”

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