Science-Watching: Forecasting New Diseases in Low-Data Settings Using Transfer Learning

[from London Mathematical Laboratory]

by Kirstin Roster, Colm Connaughton & Francisco A. Rodrigues

Abstract

Recent infectious disease outbreaks, such as the COVID-19 pandemic and the Zika epidemic in Brazil, have demonstrated both the importance and difficulty of accurately forecasting novel infectious diseases. When new diseases first emerge, we have little knowledge of the transmission process, the level and duration of immunity to reinfection, or other parameters required to build realistic epidemiological models. Time series forecasts and machine learning, while less reliant on assumptions about the disease, require large amounts of data that are also not available in early stages of an outbreak. In this study, we examine how knowledge of related diseases can help make predictions of new diseases in data-scarce environments using transfer learning. We implement both an empirical and a synthetic approach. Using data from Brazil, we compare how well different machine learning models transfer knowledge between two different dataset pairs: case counts of (i) dengue and Zika, and (ii) influenza and COVID-19. In the synthetic analysis, we generate data with an SIR model using different transmission and recovery rates, and then compare the effectiveness of different transfer learning methods. We find that transfer learning offers the potential to improve predictions, even beyond a model based on data from the target disease, though the appropriate source disease must be chosen carefully. While imperfect, these models offer an additional input for decision makers for pandemic response.

Introduction

Epidemic models can be divided into two broad categories: data-driven models aim to fit an epidemic curve to past data in order to make predictions about the future; mechanistic models simulate scenarios based on different underlying assumptions, such as varying contact rates or vaccine effectiveness. Both model types aid in the public health response: forecasts serve as an early warning system of an outbreak in the near future, while mechanistic models help us better understand the causes of spread and potential remedial interventions to prevent further infections. Many different data-driven and mechanistic models were proposed during the early stages of the COVID-19 pandemic and informed decision-making with varying levels of success. This range of predictive performance underscores both the difficulty and importance of epidemic forecasting, especially early in an outbreak. Yet the COVID-19 pandemic also led to unprecedented levels of data-sharing and collaboration across disciplines, so that several novel approaches to epidemic forecasting continue to be explored, including models that incorporate machine learning and real-time big data data streams. In addition to the COVID-19 pandemic, recent infectious disease outbreaks include Zika virus in Brazil in 2015, Ebola virus in West Africa in 2014–16, Middle East respiratory syndrome (MERS) in 2012, and coronavirus associated with severe acute respiratory syndrome (SARS-CoV) in 2003. This trajectory suggests that further improvements to epidemic forecasting will be important for global public health. Exploring the value of new methodologies can help broaden the modeler’s toolkit to prepare for the next outbreak. In this study, we consider the role of transfer learning for pandemic response.

Transfer learning refers to a collection of techniques that apply knowledge from one prediction problem to solve another, often using machine learning and with many recent applications in domains such as computer vision and natural language processing. Transfer learning leverages a model trained to execute a particular task in a particular domain, in order to perform a different task or extrapolate to a different domain. This allows the model to learn the new task with less data than would normally be required, and is therefore well-suited to data-scarce prediction problems. The underlying idea is that skills developed in one task, for example the features that are relevant to recognize human faces in images, may be useful in other situations, such as classification of emotions from facial expressions. Similarly, there may be shared features in the patterns of observed cases among similar diseases.

The value of transfer learning for the study of infectious diseases is relatively under-explored. The majority of existing studies on diseases remain in the domain of computer vision and leverage pre-trained neural networks to make diagnoses from medical images, such as retinal diseases, dental diseases, or COVID-19. Coelho and colleagues (2020) explore the potential of transfer learning for disease forecasts. They train a Long Short-Term Memory (LSTM) neural network on dengue fever time series and make forecasts directly for two other mosquito-borne diseases, Zika and Chikungunya, in two Brazilian cities. Even without any data on the two target diseases, their model achieves high prediction accuracy four weeks ahead. Gautam (2021) uses COVID-19 data from Italy and the USA to build an LSTM transfer model that predicts COVID-19 cases in countries that experienced a later pandemic onset.

These studies provide empirical evidence that transfer learning may be a valuable tool for epidemic forecasting in low-data situations, though research is still limited. In this study, we aim to contribute to this empirical literature not only by comparing different types of knowledge transfer and forecasting algorithms, but also by considering two different pairs of endemic and novel diseases observed in Brazilian cities, specifically (i) dengue and Zika, and (ii) influenza and COVID-19. With an additional analysis on simulated time series, we hope to provide theoretical guidance on the selection of appropriate disease pairs, by better understanding how different characteristics of the source and target diseases affect the viability of transfer learning.

Zika and COVID-19 are two recent examples of novel emerging diseases. Brazil experienced a Zika epidemic in 2015–16 and the WHO declared a public health emergency of global concern in February 2016. Zika is caused by an arbovirus spread primarily by mosquitoes, though other transmission methods, including congenital and sexual have also been observed. Zika belongs to the family of viral hemorrhagic fevers and symptoms of infection share some commonalities with other mosquito-borne arboviruses, such as yellow fever, dengue fever, or chikungunya. Illness tends to be asymptomatic or mild but can lead to complications, including microcephaly and other brain defects in the case of congenital transmission.

Given the similarity of the pathogen and primary transmission route, dengue fever is an appropriate choice of source disease for Zika forecasting. Not only does the shared mosquito vector result in similar seasonal patterns of annual outbreaks, but consistent, geographically and temporally granular data on dengue cases is available publicly via the open data initiative of the Brazilian government.

COVID-19 is an acute respiratory infection caused by the novel coronavirus SARS-CoV-2, which was first detected in Wuhan, China, in 2019. It is transmitted directly between humans via airborne respiratory droplets and particles. Symptoms range from mild to severe and may affect the respiratory tract and central nervous system. Several variants of the virus have emerged, which differ in their severity, transmissibility, and level of immune evasion.

Influenza is also a contagious respiratory disease that is spread primarily via respiratory droplets. Infection with the influenza virus also follows patterns of human contact and seasonality. There are two types of influenza (A and B) and new strains of each type emerge regularly. Given the similarity in transmission routes and to a lesser extent in clinical manifestations, influenza is chosen as the source disease for knowledge transfer to model COVID-19.

For each of these disease pairs, we collect time series data from Brazilian cities. Data on the target disease from half the cities is retained for testing. To ensure comparability, the test set is the same for all models. Using this empirical data, as well as the simulated time series, we implement the following transfer models to make predictions.

  • Random forest: First, we implement a random forest model which was recently found to capture well the time series characteristics of dengue in Brazil. We use this model to make predictions for Zika without re-training. We also train a random forest model on influenza data to make predictions for COVID-19. This is a direct transfer method, where models are trained only on data from the source disease.
  • Random forest with TrAdaBoost: We then incorporate data from the target disease (i.e., Zika and COVID-19) using the TrAdaBoost algorithm together with the random forest model. This is an instance-based transfer learning method, which selects relevant examples from the source disease to improve predictions on the target disease.
  • Neural network: The second machine learning algorithm we deploy is a feed-forward neural network, which is first trained on data of the endemic disease (dengue/influenza) and applied directly to forecast the new disease.
  • Neural network with re-training and fine-tuning: We then retrain only the last layer of the neural network using data from the new disease and make predictions on the test set. Finally, we fine-tune all the layers’ parameters using a small learning rate and low number of epochs. These models are examples of parameter-based transfer methods, since they leverage the weights generated by the source disease model to accelerate and improve learning in the target disease model.
  • Aspirational baseline: We compare these transfer methods to a model trained only on the target disease (Zika/COVID-19) without any data on the source disease. Specifically, we use half the cities in the target dataset for training and the other half for testing. This gives a benchmark of the performance in a large-data scenario, which would occur after a longer period of disease surveillance.

The remainder of this paper is organized as follows. The models are described in more technical detail in Section 2. Section 3 shows the results of the synthetic and empirical predictions. Finally, Section 4 discusses practical implications of the analyses.

Access the full paper [via institutional access or paid download].

Nature Portfolio Collection: Nature Mental Health

[from Nature]

To mark the upcoming launch of Nature Mental Health, and to showcase the potential breadth and scope of the journal, the editors present a collection of recent and representative mental health-themed articles from across the Nature portfolio.

In this Nature portfolio collection:

Read the full collection [some articles require a subscription].

Coronavirus Update: Fall Boosters Could Have Bits of Omicron

[from ScienceNews Coronavirus Update, by Erin Garcia de Jesús]

For all the coronavirus variants that have thrown pandemic curve balls—including alpha, beta, gamma, deltaCOVID-19 vaccines have stayed the same. That could change this fall.

Yesterday, an advisory committee to the U.S. Food and Drug Administration met to discuss whether vaccine developers should update their jabs to include a portion of the omicron variant—the version of the coronavirus that currently dominates the globe. The verdict: The omicron variant is different enough that it’s time to change the vaccines. Exactly how is up in the air; the FDA still has to weigh in and decide what versions of the coronavirus will be in the shot.

“This doesn’t mean that we are saying that there will be boosters recommended for everyone in the fall,” Amanda Cohn, chief medical officer for vaccine policy at the U.S. Centers for Disease Control and Prevention said at the June 28 advisory meeting. “But my belief is that this gives us the right vaccine for preparation for boosters in the fall.”

The decision to update COVID-19 vaccines didn’t come out of nowhere. In the two-plus years that the coronavirus has been spreading around the world, it has had a few “updates” of its own—mutating some of its proteins that allow the virus to more effectively infect our cells or hide from our immune systems.

Vaccine developers had previously crafted vaccines to tackle the beta variant that was first identified in South Africa in late 2020. Those were scrapped after studies showed that current vaccines remained effective.

The current vaccines gave our immune systems the tools to recognize variants such as beta and alpha, which each had a handful of changes from the original SARS-CoV-2 virus that sparked the pandemic. But the omicron variant is a slipperier foe. Lots more viral mutations combined with our own waning immunity mean that omicron can gain a foothold in the body. And vaccine protection isn’t as good as it once was at fending off COVID-19 symptoms.

The shots still largely protect people from developing severe symptoms, but there has been an uptick in hospitalizations and deaths among older age groups, Heather Scobie, deputy team lead of the CDC’s Surveillance and Analytics Epidemiology Task Force said at the meeting. And while it’s impossible to predict the future, we could be in for a tough fall and winter, epidemiologist Justin Lessler of the University of North Carolina at Chapel Hill said at the meeting. From March 2022 to March 2023, simulations project that deaths from COVID-19 in the United States might number in the tens to hundreds of thousands.

A switch to omicron-containing jabs may give people an extra layer of protection for the upcoming winter. PfizerBioNTech presented data at the meeting showing that updated versions of its mRNA shot gave clinical trial participants a boost of antibodies that recognize omicron. One version included omicron alone, while the other is a twofer, or bivalent, jab that mixes the original formulation with omicron. Moderna’s bivalent shot boosted antibodies too. Novavax, which developed a protein-based vaccine that the FDA is still mulling whether to authorize for emergency use, doesn’t have an omicron-based vaccine yet, though the company said its original shot gives people broad protection, generating antibodies that probably will recognize omicron.

Pfizer and Moderna both updated their vaccines using a version of omicron called BA.1, which was the dominant variant in the United States in December and January. But BA.1 has siblings and has already been outcompeted by some of them.

Since omicron first appeared late last year, “we’ve seen a relatively troubling, rapid evolution of SARS-CoV-2,” Peter Marks, director of the FDA’s Center for Biologics Evaluation and Research in Silver Spring, Maryland, said at the advisory meeting.

Now, omicron subvariants BA.2, BA.2.12.1, BA.4 and BA.5 are the dominant versions in the United States and other countries. The CDC estimates that roughly half of new U.S. infections the week ending June 25 were caused by either BA.4 or BA.5. By the time the fall rolls around, yet another new version of omicron—or a different variant entirely—may join their ranks. The big question is which of these subvariants to include in the vaccines to give people the best protection possible.

BA.1, the version already in the updated vaccines, may be the right choice, virologist Kanta Subbarao said at the FDA meeting. An advisory committee to the World Health Organization, which Subbarao chairs, recommended on June 17 that vaccines may need to be tweaked to include omicron, likely BA.1. “We’re not trying to match [what variants] may circulate,” Subbarao said. Instead, the goal is to make sure that the immune system is as prepared as possible to recognize a wide variety of variants, not just specific ones. The hope is that the broader the immune response, the better our bodies will be at fighting the virus off even as it evolves.

The variant that is farthest removed from the original virus is probably the best candidate to accomplish that goal, said Subbarao, who is director of the WHO’s Collaborating Center for Reference and Research on Influenza at the Doherty Institute in Melbourne, Australia. Computational analyses of how antibodies recognize different versions of the coronavirus suggest that BA.1 is probably the original coronavirus variant’s most distant sibling, she said.

Some members of the FDA advisory committee disagreed with choosing BA.1, instead saying that they’d prefer vaccines that include a portion of BA.4 or BA.5. With BA.1 largely gone, it may be better to follow the proverbial hockey puck where it’s going rather than where it’s been, said Bruce Gellin, chief of Global Public Health Strategy with the Rockefeller Foundation in Washington, D.C. Plus, BA.4 and BA.5 are also vastly different from the original variant. Both BA.4 and BA.5 have identical spike proteins, which the virus uses to break into cells and the vaccines use to teach our bodies to recognize an infection. So when it comes to making vaccines, the two are somewhat interchangeable.

There are some real-world data suggesting that current vaccines offer the least amount of protection from BA.4 and BA.5 compared with other omicron subvariants, Marks said. Pfizer also presented data showing results from a test in mice of a bivalent jab with the original coronavirus strain plus BA.4/BA.5. The shot sparked a broad immune response that boosted antibodies against four omicron subvariants. It’s unclear what that means for people.

Not everyone on the FDA advisory committee agreed that an update now is necessary—two members voted against it. Pediatrician Henry Bernstein of Zucker School of Medicine at Hofstra/Northwell in Uniondale, N.Y., noted that the current vaccines are still effective against severe disease and that there aren’t enough data to show that any changes would boost vaccine effectiveness. Pediatric infectious disease specialist Paul Offit of Children’s Hospital of Philadelphia said that he agrees that vaccines should help people broaden their immune responses, but he’s not yet convinced omicron is the right variant for it.

Plenty of other open questions remain too. The FDA could authorize either a vaccine that contains omicron alone or a bivalent shot, although some data hinted that a bivalent dose might spark immunity that could be more durable. Pfizer and Moderna tested their updated shots in adults. It’s unclear what the results mean for kids. Also unknown is whether people who have never been vaccinated against COVID-19 could eventually start with such an omicron-based vaccine instead of the original two doses.

Maybe researchers will get some answers before boosters start in the fall. But health agencies need to make decisions now so vaccine developers have a chance to make the shots in the first place. Unfortunately, we’re always lagging behind the virus, said pediatrician Hayley Gans of Stanford University. “We can’t always wait for the data to catch up.”

New Ultrathin Capacitor Could Enable Energy-Efficient Microchips

Scientists turn century-old material into a thin film for next-gen memory and logic devices

[from Berkeley Lab, by Rachel Berkowitz]

Electron microscope images show the precise atom-by-atom structure of a barium titanate (BaTiO3) thin film sandwiched between layers of strontium ruthenate (SrRuO3) metal to make a tiny capacitor. (Credit: Lane Martin/Berkeley Lab)

The silicon-based computer chips that power our modern devices require vast amounts of energy to operate. Despite ever-improving computing efficiency, information technology is projected to consume around 25% of all primary energy produced by 2030. Researchers in the microelectronics and materials sciences communities are seeking ways to sustainably manage the global need for computing power.

The holy grail for reducing this digital demand is to develop microelectronics that operate at much lower voltages, which would require less energy and is a primary goal of efforts to move beyond today’s state-of-the-art CMOS (complementary metaloxide semiconductor) devices.

Non-silicon materials with enticing properties for memory and logic devices exist; but their common bulk form still requires large voltages to manipulate, making them incompatible with modern electronics. Designing thin-film alternatives that not only perform well at low operating voltages but can also be packed into microelectronic devices remains a challenge.

Now, a team of researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) and UC Berkeley have identified one energy-efficient route—by synthesizing a thin-layer version of a well-known material whose properties are exactly what’s needed for next-generation devices.

First discovered more than 80 years ago, barium titanate (BaTiO3) found use in various capacitors for electronic circuits, ultrasonic generators, transducers, and even sonar.

Crystals of the material respond quickly to a small electric field, flip-flopping the orientation of the charged atoms that make up the material in a reversible but permanent manner even if the applied field is removed. This provides a way to switch between the proverbial “0” and “1” states in logic and memory storage devices—but still requires voltages larger than 1,000 millivolts (mV) for doing so.

Seeking to harness these properties for use in microchips, the Berkeley Lab-led team developed a pathway for creating films of BaTiO3 just 25 nanometers thin—less than a thousandth of a human hair’s width—whose orientation of charged atoms, or polarization, switches as quickly and efficiently as in the bulk version.

“We’ve known about BaTiO3 for the better part of a century and we’ve known how to make thin films of this material for over 40 years. But until now, nobody could make a film that could get close to the structure or performance that could be achieved in bulk,” said Lane Martin, a faculty scientist in the Materials Sciences Division (MSD) at Berkeley Lab and professor of materials science and engineering at UC Berkeley who led the work.

Historically, synthesis attempts have resulted in films that contain higher concentrations of “defects”—points where the structure differs from an idealized version of the material—as compared to bulk versions. Such a high concentration of defects negatively impacts the performance of thin films. Martin and colleagues developed an approach to growing the films that limits those defects. The findings were published in the journal Nature Materials.

To understand what it takes to produce the best, low-defect BaTiO3 thin films, the researchers turned to a process called pulsed-laser deposition. Firing a powerful beam of an ultraviolet laser light onto a ceramic target of BaTiO3 causes the material to transform into a plasma, which then transmits atoms from the target onto a surface to grow the film. “It’s a versatile tool where we can tweak a lot of knobs in the film’s growth and see which are most important for controlling the properties,” said Martin.

Martin and his colleagues showed that their method could achieve precise control over the deposited film’s structure, chemistry, thickness, and interfaces with metal electrodes. By chopping each deposited sample in half and looking at its structure atom by atom using tools at the National Center for Electron Microscopy at Berkeley Lab’s Molecular Foundry, the researchers revealed a version that precisely mimicked an extremely thin slice of the bulk.

“It’s fun to think that we can take these classic materials that we thought we knew everything about, and flip them on their head with new approaches to making and characterizing them,” said Martin.

Finally, by placing a film of BaTiO3 in between two metal layers, Martin and his team created tiny capacitors—the electronic components that rapidly store and release energy in a circuit. Applying voltages of 100 mV or less and measuring the current that emerges showed that the film’s polarization switched within two billionths of a second and could potentially be faster—competitive with what it takes for today’s computers to access memory or perform calculations.

The work follows the bigger goal of creating materials with small switching voltages, and examining how interfaces with the metal components necessary for devices impact such materials. “This is a good early victory in our pursuit of low-power electronics that go beyond what is possible with silicon-based electronics today,” said Martin.

“Unlike our new devices, the capacitors used in chips today don’t hold their data unless you keep applying a voltage,” said Martin. And current technologies generally work at 500 to 600 mV, while a thin film version could work at 50 to 100 mV or less. Together, these measurements demonstrate a successful optimization of voltage and polarization robustness—which tend to be a trade-off, especially in thin materials.

Next, the team plans to shrink the material down even thinner to make it compatible with real devices in computers and study how it behaves at those tiny dimensions. At the same time, they will work with collaborators at companies such as Intel Corp. to test the feasibility in first-generation electronic devices. “If you could make each logic operation in a computer a million times more efficient, think how much energy you save. That’s why we’re doing this,” said Martin.

This research was supported by the U.S. Department of Energy (DOE) Office of Science. The Molecular Foundry is a DOE Office of Science user facility at Berkeley Lab.

Science-Watching: Nature webinar

Cryo-EM and artificial intelligence: A marriage made in cell extracts

Date: Thursday, June 16, 2022

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This webcast has been produced on behalf of Nature’s sponsor who retains sole responsibility for content. About this content.

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Deep insights into how cellular proteins interact have been out of reach, especially in a native context. In this webcast, Dr. Panagiotis Kastritis of Martin Luther University Halle-Wittenberg will describe how analysis of endogenous cell extracts with cryo-EM and artificial intelligence methods can provide integrated biological analysis of protein communities in a closer-to-native setting.

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Science-Watching: High-Energy Physics (CERN Courier – May/June 2022)

[from CERN Courier – May/June 2022, by Matthew Chalmers, editor]

As the LHC beams prepare to set new records in brightness and energy, the Courier takes an in-depth look at the Run 3 physics prospects in searches, precision measurements, flavor and heavy-ion physics. Together with a diverse fixed-target program, the LHC experiments are forging new research directions, while recent developments advance the feasibility study for a possible Future Circular Collider.

Also in the issue: a massive surprise from CDF, intriguing results at Moriond, luminosity versus energy, the CERN Neutrino Platform, International Linear Collider, and much more.

Read the May/June 2022 issue [archived PDF].

Climatology-Watching: Tyndall Centre for Climate Change Research

[from Tyndall Centre for Climate Change Research]

UK’s climate change readiness has made ‘significant progress’

by Renee Karunungan on May 4, 2022

There is significant progress in the UK for reporting and implementing climate change adaptation, according to a new study led by Tyndall UEA’s Katie Jenkins. Katie has created an Adaptation Inventory of adaptation actions happening based on official records of adaptation projects being implemented by both public and private sector, accompanied by  a systematic review of the peer-reviewed literature of adaptation case studies.

Adapting to climate change means taking action to prepare for and adjust to current and predicted effects of climate change. Adaptation plays an important role in managing past, present and future climate risk and impacts. However, there is an “adaptation gap” where the distance between existing adaptation efforts versus adaptation needs is widening, according to the United Nations Environment Programme’s Adaptation Gap Report. Tracking national adaptation plans is deemed critical to support future decision-making and drive future actions.

Studies of adaptation consider the UK at the forefront of adaptation planning, setting an early example with the Climate Change Act 2008 which contains a five-year cycle of adaptation planning, published as the UK Climate Change Risk Assessment. Evidence from the UK Climate Change Committee shows that adaptation action has failed to keep pace with increasing climate risks. 

According to the Committee’s assessment, adaptation planning for 2C and 4C global warming is not happening, and that the gap between future risks and planned adaptation has widened, delivering the minimum level of resilience.

Katie’s new Adaptation Inventory provides insight on what is currently being implemented, which helps policymakers and practitioners learn from existing knowledge and practical case studies.

“The Adaptation Inventory provides a consistent and easily searchable database which will continue to evolve. It can provide evidence on the specific types of adaptation implemented on the ground as well as provide more detailed insight into the specific examples of action being implemented. This has the potential to help and inform UK-based decision-making,” Katie said.

The Adaptation Inventory identifies and documents current and planned adaptation in the UK, and how it is being implemented through adaptation actions, the sectors where adaptation is occurring, and where the gaps remain. There were 360 adaptation actions identified in the Inventory, comprising 134 adaptation types. Out of these 360 adaptation actions, 80% have already been implemented.

The private sector accounts for 74% of the actions with water companies dominating. Regulatory frameworks, standards, and reporting requirements are key drivers required by water companies by the Regulator. For example, water companies are already required to plan their resilience to drought.

The most common types of adaptation actions are flood protection (12%), leakage reduction (4%), water metering (3%), property level flood protection (3%), operational improvements (3%), and back-up generators (3%). Most actions were categorized as structural and physical interventions. Other interventions were categorized as technological and ecosystem based. 

An example of a structural adaptation action is raising boat landings to address higher tides because of rising sea levels. For an example of technology, London Transport has installed air cooling units and mechanical chillers at two key busy tube stations to address heat stress. An ecosystem-based example  introduces barley straw to reservoirs to control blue green algae, more common with warmer summers.

The Adaptation Inventory also looks at the types of climate hazards being addressed. It found that 76% of the actions were in response to drought, 26% for extreme rainfall, 13% for flooding, and 11% for higher temperatures. One example of adaptation for drought is rainwater recovery using storage facilities available on the site, reducing the demand for fresh water during drought. For alleviating flooding, a water company is using afforestation. The London Underground has doubled the capacity of ventilation shafts on the Victoria line, which provide more air flow on hot days.

Pathogens-Watching

New Articles in PLOS Pathogens

Insertive Condom-Protected and Condomless Vaginal Sex Both Have a Profound Impact on the Penile Immune Correlates of HIV Susceptibility

by Avid Mohammadi, Sareh Bagherichimeh, Yoojin Choi, Azadeh Fazel, Elizabeth Tevlin, Sanja Huibner, Zhongtian Shao, David Zuanazzi, Jessica L. Prodger, Sara V. Good, Wangari Tharao & Rupert Kaul

Summary: In heterosexual men, the penis is the primary site of Human Immunodeficiency Virus (HIV) acquisition. Levels of inflammatory cytokines in the coronal sulcus are associated with an increased HIV risk, and we hypothesized that these may be altered after insertive penile sex. Therefore, we designed the Sex, Couples and Science Study (SECS study) to define the impact of penilevaginal sex on the penile immune correlates of HIV susceptibility. We found that multiple coronal sulcus cytokines increased dramatically and rapidly after sex, regardless of condom use, with a return to baseline levels by 72 hours. The changes observed after condomless sex were strongly predicted by cytokine concentrations in the vaginal secretions of the female partner, and were similar in circumcised and uncircumcised men. We believe that these findings have important implications for understanding the immunopathogenesis of penile HIV acquisition; in addition, they have important implications for the design of clinical studies of penile HIV acquisition and prevention.

[Archived PDF]

Engineering, Decoding and Systems-Level Characterization of Chimpanzee Cytomegalovirus

by Quang Vinh Phan, Boris Bogdanow, Emanuel Wyler, Markus Landthaler, Fan Liu, Christian Hagemeier & Lüder Wiebusch

Summary: Human cytomegalovirus (HCMV) infection is associated with systemic disease in immunocompromised individuals and congenitally infected neonates. Animal CMVs and their bacterial artificial chromosome (BAC) clones have been utilized as models for CMV infection and thereby contributed immensely to the understanding of pathogenesis, host immune response and underlying molecular mechanism of CMV infections. As the closest relative to HCMV, the chimpanzee CMV (CCMV) holds a great potential as a model system for HCMV infection but its application was limited due to the lack of tools and data for functional genomic analyses. Here, the cloning of the CCMV as a BAC vector made its viral genome available to gene targeting techniques that allow the efficient application of reverse genetic strategies. Furthermore, the multi-omic datasets created in this study provide an in-depth view of the viral gene repertoire and the host cell responses to infection, confirming the close phylogenetic relationship between HCMV and CCMV on a system level. Taken together, the newly established CCMVBAC system presents a framework for HCMV modeling and comparative studies to address key questions in evolutionary processes and infection mechanisms.

[Archived PDF]

RplI Interacts with 5′ UTR of exsA to Repress Its Translation and Type III Secretion System in Pseudomonas aeruginosa

by Dan Wang, Xinxin Zhang, Liwen Yin, Qi Liu, Zhaoli Yu, Congjuan Xu, Zhenzhen Ma, Yushan Xia, Jing Shi, Yuehua Gong, Fang Bai, Zhihui Cheng, Weihui Wu, Jinzhong Lin & Yongxin Jin

Summary: Ribosomes provide all living organisms the capacity to synthesize proteins. The production of many ribosomal proteins is often controlled by an autoregulatory feedback mechanism. Paeruginosa is an opportunistic human pathogen and its type III secretion system (T3SS) is a critical virulence determinant in host infections. In this study, by screening a Tn5 mutant library, we identified rplI, encoding ribosomal large subunit protein L9, as a novel repressor for the T3SS. Further exploring the regulatory mechanism, we found that the RplI protein interacts with the 5’ UTR (5’ untranslated region) of exsA, a gene coding for transcriptional activator of the T3SS. Such an interaction likely blocks ribosome loading on the exsA 5’ UTR, inhibiting the initiation of exsA translation. The significance of this work is in the identification of a novel repressor for the T3SS and elucidation of its molecular mechanism. Furthermore, this work provides evidence for individual ribosomal protein regulating mRNA translation beyond its autogenous feedback control.

[Archived PDF]

Structure of a Bacterial Rhs Effector Exported by the Type VI Secretion System

by Patrick Günther, Dennis Quentin, Shehryar Ahmad, Kartik Sachar, Christos Gatsogiannis, John C. Whitney & Stefan Raunser

Summary: Bacteria have developed a variety of strategies to compete for nutrients and limited resources. One system widely used by Gram-negative bacteria is the T6 secretion system which delivers a plethora of effectors into competing bacterial cells. Known functions of effectors are degradation of the cell wall, the depletion of essential metabolites such as NAD+ or the cleavage of DNA. RhsA is an effector from the widespread plant-protecting bacteria Pseudomonas protegens. We found that RhsA forms a closed cocoon similar to that found in bacterial Tc toxins and metazoan teneurin proteins. The effector cleaves its polypeptide chain by itself in three pieces, namely the N-terminal domain including a seal, the cocoon and the actual toxic component which potentially cleaves DNA. The toxic component is encapsulated in the large cocoon, so that the effector producing bacterium is protected from the toxin. In order for the toxin to exit the cocoon, we propose that the seal, which closes the cocoon at one end, is removed by mechanical forces during injection of the effector by the T6 secretion system. We further hypothesize about different scenarios for the delivery of the toxin into the cytoplasm of the host cell. Together, our findings expand the knowledge of the mechanism of action of the T6 secretion system and its essential role in interbacterial competition.

[Archived PDF]

Non-Neutralizing Antibodies Targeting the Immunogenic Regions of HIV-1 Envelope Reduce Mucosal Infection and Virus Burden in Humanized Mice

by Catarina E. Hioe, Guangming Li, Xiaomei Liu, Ourania Tsahouridis, Xiuting He, Masaya Funaki, Jéromine Klingler, Alex F. Tang, Roya Feyznezhad, Daniel W. Heindel, Xiao-Hong Wang, David A. Spencer, Guangnan Hu, Namita Satija, Jérémie Prévost, Andrés Finzi, Ann J. Hessell, Shixia Wang, Shan Lu, Benjamin K. Chen, Susan Zolla-Pazner, Chitra Upadhyay, Raymond Alvarez & Lishan Su

Summary: In the past decade, HIV-1 has infected an estimated 1.5 to 2 million people every year, but vaccines needed to control this pandemic are unavailable. Among vaccines tested in the human efficacy trials, the RV144 vaccine regimen showed a modest efficacy and revealed non-neutralizing antibodies against the virus envelope glycoproteins as a correlate of reduced virus acquisition. To design more efficacious HIV-1 vaccines, a better understanding about antiviral mechanisms of these antibodies is needed. Here non-neutralizing monoclonal antibodies against two immunogenic sites on the virus envelope were evaluated for passive administration to humanized mice that were subsequently challenged with HIV-1. The antibodies did not block mucosal HIV-1 infection but reduced virus burden. The level of virus reduction correlated with the antibody binding potency and the effector functions mediated through their Fc fragments, which included antibody-dependent phagocytosis and complement activation, but not the commonly studied antibody-dependent cellular cytotoxicity. The importance of the Fc functions was further demonstrated by reduced virus control when mutations were introduced to decrease Fc activities. This study provides new evidence for the important contribution of multiple Fc-dependent antibody functions in immune control against HIV-1.

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Variability in an Effector Gene Promoter of a Necrotrophic Fungal Pathogen Dictates Epistasis and Effector-Triggered Susceptibility in Wheat

by Evan John, Silke Jacques, Huyen T. T. Phan, Lifang Liu, Danilo Pereira, Daniel Croll, Karam B. Singh, Richard P. Oliver & Kar-Chun Tan

Summary: Breeding for durable resistance to fungal diseases in crops is a continual challenge for crop breeders. Fungal pathogens evolve ways to overcome host resistance by masking themselves through effector evolution and evasion of broad-spectrum defense responses. Association studies on mapping populations infected by isolate mixtures are often used by researchers to seek out novel sources of genetic resistance. Disease resistance quantitative trait loci (QTL) are often minor or inconsistent across environments. This is a particular problem with septoria diseases of cereals such as septoria nodorum blotch (SNB) of wheat caused by Parastagonospora nodorum. The fungus uses a suite of necrotrophic effectors (NEs) to cause SNB. We characterized a genetic element, called PE401, in the promoter of the major NE gene Tox1, which is present in some Pnodorum isolates. PE401 functions as a transcriptional repressor of Tox1 and exerts epistatic control on another major SNB resistance QTL in the host. In the context of crop protection, constant surveillance of the pathogen population for the frequency of PE401 in conjunction with NE diversity will enable agronomists to provide the best advice to growers on which wheat varieties can be tailored to provide optimal SNB resistance to regional pathogen population genotypes.

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Mutational Analysis of Aedes aegypti Dicer 2 Provides Insights into the Biogenesis of Antiviral Exogenous Small Interfering RNAs

by Rommel J. Gestuveo, Rhys Parry, Laura B. Dickson, Sebastian Lequime, Vattipally B. Sreenu, Matthew J. Arnold, Alexander A. Khromykh, Esther Schnettler, Louis Lambrechts, Margus Varjak & Alain Kohl

Summary: Aedes aegypti mosquitoes that transmit human-pathogenic viruses rely on the exogenous small interfering RNA (exo-siRNA) pathway as part of antiviral responses. This pathway is triggered by virus-derived double-stranded RNA (dsRNA) produced during viral replication that is then cleaved by Dicer 2 (Dcr2) into virus-derived small interfering RNAs (vsiRNAs). These vsiRNAs target viral RNA, leading to suppression of viral replication. The importance of Dcr2 in this pathway has been intensely studied in the Drosophila melanogaster model but is largely lacking in mosquitoes. Here, we have identified conserved and functionally relevant amino acids in the helicase and RNase III domains of Aeaegypti Dcr2 that are important in its silencing activity and antiviral responses against Semliki Forest virus (SFV). Small RNA sequencing of SFV-infected mosquito cells with functional or mutated Dcr2 gave new insights into the nature and origin of vsiRNAs. The findings of this study, together with the different molecular tools we have previously developed to investigate the exo-siRNA pathway of mosquito cells, have started to uncover important properties of Dcr2 that could be valuable in understanding mosquito-arbovirus interactions and potentially in developing or assisting vector control strategies.

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Probing the Structure and Function of the Protease Domain of Botulinum Neurotoxins Using Single-Domain Antibodies

by Kwok-ho Lam, Jacqueline M. Tremblay, Kay Perry, Konstantin Ichtchenko, Charles B. Shoemaker & Rongsheng Jin

Summary: Botulinum neurotoxins (BoNTs) are extremely toxic to humans by causing flaccid paralysis of botulism. The catalytic light chain (LC) of BoNTs is the warhead of the toxin, which is mainly responsible for BoNT’s neurotoxic effects. As an endopeptidase, LC is delivered by the toxin to inside neurons where it specifically cleaves neuronal SNARE proteins and causes muscle paralysis. While the currently available equine and human antitoxin sera can prevent further intoxication, they do not promote recovery from paralysis that has already occurred. We strike to develop single-domain variable heavy-chain (VHH) antibodies targeting the LC of BoNT/A (LC/A) and BoNT/B (LC/B) as antidotes to inhibit or eliminate the intraneuronal LC protease. Here, we report the identification and characterization of large panels of new and unique VHHs that bind to LC/A or LC/B. Using a combination of X-ray crystallography and biochemical assays, we reveal that VHHs exploit diverse mechanisms to interact with LC/A and LC/B and inhibit their protease activity, and such knowledge can be harnessed to predict their specificity towards different toxin subtypes within each serotype. We anticipate that the new VHHs and their characterization reported here will contribute to the development of improved botulism therapeutics having high potencies and broad specificities.

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B Cell Overexpression of FCRL5 and PD-1 Is Associated with Low Antibody Titers in HCV Infection

by Clinton O. Ogega, Nicole E. Skinner, Andrew I. Flyak, Kaitlyn E. Clark, Nathan L. Board, Pamela J. Bjorkman, James E. Crowe Jr., Andrea L. Cox, Stuart C. Ray & Justin R. Bailey

Summary: Antiviral immunity relies on production of protective immunoglobulin G (IgG) by B cells, but many hepatitis C virus (HCV)-infected individuals have very low levels of HCV-specific IgG in their serum. Elucidating mechanisms underlying this suboptimal IgG expression remains paramount in guiding therapeutic and vaccine strategies. In this study, we developed a highly specific method to capture HCV-specific B cells and characterized their surface protein expression. Two proteins analyzed were Fc receptor-like protein 5 (FCRL5), a cell surface receptor for IgG, and programmed cell death protein-1 (PD-1), a marker of lymphocyte activation and exhaustion. We measured serum levels of anti-HCV IgG in these subjects and demonstrated that overexpression of FCRL5 and PD-1 on memory B cells was associated with reduced anti-E2 IgG levels. This study uses HCV as a viral model, but the findings may be applicable to many viral infections, and they offer new potential targets to enhance antiviral IgG production.

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Following COVID-19 Evolution Carefully

JAMA Online First: Booster Vaccination to Reduce SARS-CoV-2 Infection

Association of a Third Dose of BNT162b2 Vaccine With Incidence of SARS-CoV-2 Infection Among Health Care Workers in Israel

by Avishay Spitzer, MD; Yoel Angel, MD, MBA; Or Marudi, MSc; et al.

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Editorial: Booster Vaccination to Reduce SARS-CoV-2 Transmission and Infection by Anna Wald, MD, MPH

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A National Strategy for the “New Normal” of Life With COVID

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False-Positive Results in Rapid Antigen Tests for SARS-CoV-2

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Characteristics and Outcomes of Hospitalized Patients in South Africa During the COVID-19 Omicron Wave

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Highlights From the American Heart Association’s Scientific Sessions—ApoB as a Risk Marker, an Oral PCSK9 Inhibitor, Aspirin and Dementia, and More

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