Microbial communities stay healthy by swapping knowledge

High levels of horizontal gene transfer could help researchers engineer useful microbiomes independent of unstable population dynamics

Peer-Reviewed Publication

DUKE UNIVERSITY

 

IMAGE: LINCHONG YOU, PROFESSOR OF BIOMEDICAL ENGINEERING AT DUKE UNIVERSITY view more 

CREDIT: DUKE UNIVERSITY

DURHAM, N.C. – Biomedical engineers at Duke University have demonstrated a microbial community phenomenon that essentially equates to teaching neighbors how to complete necessary tasks by ripping out and sharing parts of the brain.

The process allows microbiomes to keep themselves and their environments healthy and could help scientists create robust, bespoke microbial systems for applications ranging from cleaning toxins from the environment to producing biofuel and other consumer products.

The research appears online September 1 in the journal Nature Chemical Biology.

Large, complex microbial communities live everywhere in the world, from rivers and mountains to humans and houses. But whether comparing microbiomes on snowcapped peaks in Asia or within the stomachs of identical human twins, the composition of species within these communities can vary widely.

No matter how different these microbiomes may appear to be on the surface, if they live in similar environments, they’re likely going to fill the same functions. One way of evaluating what processes they’re carrying out is focusing on the genes that encode the functions rather than the species themselves.

“If you count the number of the copies of genes that encode some function, their numbers can remain stable even if the species composition of the community changes dramatically,” said Lingchong You, professor of biomedical engineering at Duke. “One important route to this level of stability is through horizontal gene transfer.”

Horizontal gene transfer is the process by which bacteria constantly share genetic recipes for new abilities by swapping packages of genetic material called plasmids. At a conceptual level, it’s not entirely dissimilar to creating a copy of a collection of neurons that knows how to make lasagna, ripping it out of your head and giving it to a friend to use.

In the new paper, You and his colleagues show that this gene transfer plays an essential role in keeping microbiomes healthy and ensuring critical tasks are completed. Starting with two different species of bacteria, the researchers controlled the levels of horizontal gene transfer and showed that higher rates led to more stable concentrations of these genes.

The team then constructed a community of up to 72 bacteria swapping up to 13 different genes simultaneously and measured the genes’ stability. As with the simpler model, the genes that were traded more frequently maintained a steadier level within the microbiome as a whole.

“These results have been speculated about before, but never quantified within living communities,” You said. “The other route to this level of redundancy is to have multiple species that can perform the same function. But a high level of horizontal gene transfer is a much more robust method to achieve the same results.”

Put another way, a construction crew could be extremely resilient to electricians quitting if the plumbers on site also knew how to wire a building. But the same crew would be even more resilient if the remaining electricians could simply transfer their expertise to anyone on the job when needed, no matter their profession.

Moving forward, You hopes to study natural microbial communities to prove definitively that this phenomenon is important to a microbiome’s health outside of a laboratory. He also plans to implement this dynamic division of labor through horizontal gene transfer in engineered microbial systems.

“There are cases where complex metabolic pathways are difficult to engineer in a single bacterial species where it’s easier to have different populations carrying out different steps of the process,” You said. “This study suggests we can implement that strategy through gene transfer so that we don’t have to worry about the specific composition of species. We can just let the community find the best balance for itself while still knowing it will continue to get the job done.”

This research is supported by the National Institutes of Health (R01AI125604, R01EB031869) and the National Science Foundation (MCB-347 1937259).

CITATION: “Horizontal Gene Transfer Enables Programmable Gene Stability in Synthetic Microbiota,” Teng Wang, Andrea Weiss, Ammara Aqeel, Feilun Wu, Allison J. Lopatkin, Lawrence A. David, Lingchong You. Nature Chemical Biology, Sept. 1, 2022. DOI: 10.1038/s41589-022-01114-3

Nature Link: https://www.nature.com/articles/s41589-022-01114-3

# # #

---

JOURNAL

Nature Chemical Biology

DOI

10.1038/s41589-022-01114-3 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Horizontal Gene Transfer Enables Programmable Gene Stability in Synthetic Microbiota

ARTICLE PUBLICATION DATE

1-Sep-2022

Disclaimer: AA

FRACKING

New study in Earth Science Frontiers suggests lacustrine shale reserves can bolster China’s energy independence

Their new study elaborates on the enrichment conditions and distribution characteristics of lacustrine shale oil in China

Peer-Reviewed Publication

CACTUS COMMUNICATIONS

 

VIDEO: THEIR NEW STUDY ELABORATES ON THE ENRICHMENT CONDITIONS AND DISTRIBUTION CHARACTERISTICS OF LACUSTRINE SHALE OIL IN CHINA view more 

CREDIT: EARTH SCIENCE FRONTIERS

Shale oil exploration has rapidly expanded since the beginning of the 21st century, particularly in North America. Since 2010, the production of marine shale oil has increased at an average rate of more than 25% annually, making the US the global leader in production with total recoverable resources pegged at approximately 20.7 billion tons. Developing shale oil resources has significant potential to shape energy security and geopolitics. In addition to marine shale oil, countries have also begun utilizing lacustrine basins for oil production.

Lacustrine shale oil reserves are deemed optimal when their organic content is high, the reservoirs feature a suitably high pressure to facilitate formation, and the Ro value, which indicates the thermal maturity of shale, is greater than 1.0%. In China, the lacustrine medium-to-high maturity shale oil is characterized by mature liquid hydrocarbons and a high proportion of movable oil. While these characteristics make it a valuable resource, questions surrounding production costs and recoverable quantities remain. Furthermore, without low development costs it remains to be seen if these reserves can be utilized economically.

Now, a group of petroleum scientists led by Dr. Wenzhi Zhao at the China National Petroleum Corporation, have presented their evaluation of the enrichment conditions and occurrence characteristics of lacustrine shale oil reservoirs in China. “We have proposed a set of evaluation parameters for shale oil enrichment zones and evaluated the occurrence of optimal areas. This data will serve as a good reference to help promote the development of these oil reserves economically,” says Dr. Zhao while explaining the motivation behind the research. This study was recently published in Earth Science Frontiers. Also visit the website for the press release based on this study: http://www.earthsciencefrontiers.net.cn/EN/news/news32.shtml.

The team utilized data collected from lacustrine medium-to-high maturity shale reserves currently being developed in China for their analyses, and specifically determined the optimal conditions for shale oil accumulation and the characteristics of these deposits. Their analysis revealed that shale with a high organic content and appropriate thermal maturity favored oil retention. “The optimal organic content of this shale ranges from three to four percent, and kerogen I and II seems to be the dominant type of organic matter. Interestingly, the Ro values of this shale were greater than 0.9%. Finally, these reservoirs must exhibit a certain degree of brittleness and have porosities between three to six percent,” says Dr. Zhao when asked to elaborate on the key findings. In addition to these parameters, shale oil with good mobility was found when large amounts of high-quality hydrocarbons were present, and the enrichment interval of this oil was highly dependent on the reservoir having a tightly sealed roof and floor.

“What we see is that major enrichment of oil occurs at semi-deep to deep depositional zones. Moreover, the distribution of shale oil enrichment intervals is governed by the type of lithologies as oil and gas is retained in the source rock. Shale assemblages are the best lithologic sections while Mudstone is not,” observes Dr. Zhao, surmising the characteristics of these shale oil deposits.

The team pegs the total shale oil reserves in China with medium-to-high maturity to be close to 16.3 billion tons of which nearly 8.4 billion tons could be developed commercially. These reserves are spread across the Ordos, Songliao, Bohai Bay, and Junggar Basins and represent a significant energy resource for China’s future. “We can now offer better guidance to reduce the number of ineffective wells and have set the stage to greatly improve the number of economic discoveries in China,” concludes Dr. Zhao optimistically and perhaps a sense of justified pride.

 

CAPTION

Their new study elaborates on the enrichment conditions and distribution characteristics of lacustrine shale oil in China

CREDIT

Earth Science Frontiers

CAPTION

Analyses from the Songliao Basin revealed a significant increase in free hydrocarbons at Ro > 0.9% due to the thermal maturity threshold of the sweet-spot for lacustrine shale oil.

CREDIT

Wenzhi Zhao from RIPED

Reference

DOI: https://doi.org/10.13745/j.esf.sf.2022.8.31-en

Authors: Wenzhi Zhao1,3, Rukai Zhu1,2, Wei Liu1,3, Congsheng Bian1,3, Kun Wang1

Affiliations  

1. Research Institute of Petroleum Exploration and Development, CNPC, Beijing 100083
2. Key Laboratory of Oil and Gas Reservoirs, CNPC
3. ZWZ Academician Research Studio, Beijing 100083

 

About Earth Science Frontiers

Earth Science Frontiers is a bimonthly peer reviewed scholarly journal co-sponsored by the China University of Geosciences (Beijing) and Peking University. It was first published in 1994, and academician Wang Chengshan is the current Editor-in-Chief. Each issue of the journal is centered on a specific geoscience topic and managed by experts in that field as Guest Editors. Each issue also contains a number of articles on self-select subjects. Articles published on Earth Science Frontiers cover all disciplines of earth sciences with emphasis on frontier and innovative basic research. At the same time, the journal also publishes research findings that may be considered contentious. Over the years, Earth Science Frontiers has won several publisher awards, including “The Internationally Most Influential Journal in Chinese Language” and “The Top 100 Outstanding Chinese Scholarly Journals.” In 2019, Earth Science Frontiers was selected among top-tier journals to join a national action plan for achieving excellence in science and technology research publishing in China.

E-mail: frontier@cugb.edu.cn
Website: http://www.earthsciencefrontiers.net.cn

 

About Dr. Wenzhi Zhao

Dr. Wenzhi Zhao is the President of PetroChina Research Institute of Petroleum Exploration and Development (RIPED), the Deputy General Manager of PetroChina Exploration & Production Company, and Research Professor at the Key Laboratory of Oil & Gas Reservoir. He earned his PhD in Mineral Resource Prospecting and Exploration from RIPED in 2003 and has published 11 monographs and over 70 academic papers. He is the recipient of several high-profile scientific awards including the Li Siguang Geological Science Medal (2003) and the First Prize of National Scientific and Technological Progress Award (2007).

---

JOURNAL

Earth Science Frontiers

DOI

10.13745/j.esf.sf.2022.8.31-en 

METHOD OF RESEARCH

Observational study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Enrichment conditions and distribution characteristics of lacustrine medium-to-high maturity shale oil in China

COI STATEMENT

None

Improving foam stability in disinfectants with high ethanol concentrations

A new study proposes a method of foam stabilization that could be used to make highly efficient hand sanitizers

Peer-Reviewed Publication

TOKYO UNIVERSITY OF SCIENCE

 

IMAGE: IN A NEW STUDY, SCIENTISTS FROM JAPAN COMBINED AN ANIONIC SURFACTANT, LONG-CHAIN ALCOHOLS, AND AN INORGANIC ELECTROLYTE TO ENHANCE THE FOAM STABILITY IN DISINFECTANTS WITH HIGH CONCENTRATION OF ETHANOL. THEIR STRATEGY CAN HELP FORMULATE HAND SANITIZERS WITH OPTIMIZED FOAM STABILITY. view more 

CREDIT: KENICHI SAKAI FROM TOKYO UNIVERSITY OF SCIENCE

Since the outbreak of COVID-19, the importance wearing masks and disinfection of items has become paramount. As a result, there is now a greater need for effective, potent, and simple-to-apply disinfectants. Foam-type disinfectants are a leading candidate in this regard since they do not drip, keep the disinfected area visible, and are less likely to reach the user’s eyes.

However, foam-type disinfectants are not without issues. While the foam is usually stabilized with the adsorption of a surfactant at the air/liquid interface, adding high concentration of ethanol, an antiseptic, to foams in aqueous solutions causes defoaming resulting from destabilization of the foam.

To improve the stability of foam disinfectants at high ethanol concentrations, a group of researchers from Tokyo University of Science (TUS), Japan, in collaboration with the Life Science Products Division, NOF Corporation, have now come up with a new proposal. This study, led by Associate Professor Kenichi Sakai of TUS, was made available online on August 04, 2022 and published in Chemistry Letters.

In their study, the team added an anionic (negatively charged) surfactant, long-chain alcohols, and an inorganic electrolyte to an aqueous solution containing 60% ethanol by volume. They used sodium methyl stearoyl taurate (SMT) as the surfactant, CnOH (where n = 12, 14, 16) as the alcohols, and magnesium sulfate (MgSO4) as the electrolyte.

The inorganic electrolyte provided two main advantages: firstly, it enabled effective screening of the electrostatic repulsion between the SMT headgroup adsorbed at the air-liquid interface. Secondly, it promoted interactions between Mg2+ ions and the headgroups. These, in turn, facilitated the additional adsorption of SMT and CnOH, increasing the surface viscosity and foam stability.

“We have been working on this research project before the novel coronavirus infection became a social problem. We believe that the social impact of this research will only increase as the social need for disinfectants and health safety go up,” says Dr. Sakai, explaining his motivation behind the study.

The team observed that, in the absence of the MgSO4, foaming occurred upon shaking for CnOH (n = 12, 14, 16) with the foam stability increasing with increasing n. Additionally, the combination of SMT and CnOH resulted in a decrease in surface tension and an increase in surface viscosity, which increased foam stability.

When MgSO4 was added, foaming happened upon vigorous shaking. The foam stability increased with increase in the mole ratio of MgSO4, which decreased the surface tension while increasing the surface viscosity.

Finally, the team used a non-pressurized commercial pump to test the foam formation of the solution. They found that the SMT and C14OH mixture produced adequate foaming both with and without MgSO4. Further, defoaming occurred after 30 seconds for both cases, an appropriate time scale for the dissipation of the foam after application.

“The COVID-19 pandemic has seriously affected human lives and social activities on a global scale. As a result, the importance of proper sanitation has been recognized worldwide. We believe that the results of our research will contribute to the sustainable development goal (SDG3) of ensuring good health and well-being among people of all ages,” says Dr. Sakai.

Indeed, the team’s samples could help formulate foam-type hand sanitizers you may be using soon!

 

***

 

Reference                     
DOI: https://doi.org/10.1246/cl.220306

About The Tokyo University of Science
Tokyo University of Science (TUS) is a well-known and respected university, and the largest science-specialized private research university in Japan, with four campuses in central Tokyo and its suburbs and in Hokkaido. Established in 1881, the university has continually contributed to Japan's development in science through inculcating the love for science in researchers, technicians, and educators.

With a mission of “Creating science and technology for the harmonious development of nature, human beings, and society", TUS has undertaken a wide range of research from basic to applied science. TUS has embraced a multidisciplinary approach to research and undertaken intensive study in some of today's most vital fields. TUS is a meritocracy where the best in science is recognized and nurtured. It is the only private university in Japan that has produced a Nobel Prize winner and the only private university in Asia to produce Nobel Prize winners within the natural sciences field.
Website: https://www.tus.ac.jp/en/mediarelations/

About Associate Professor Kenichi Sakai from Tokyo University of Science
Dr. Kenichi Sakai is an Associate Professor at the Tokyo University of Science, Japan, where he is a member of the Faculty of Science and Technology in the Department of Pure and Applied Chemistry. His research interests lie in the field of physical chemistry, particularly in colloid and interface chemistry. He has over 160 publications to his name and has received several awards, including the Young Scientist Award from the Division of Colloid and Surface Chemistry, The Chemical Society of Japan in 2015, and the Coating Societies International Medallion in 2007.

Funding information
This study was supported by the JST A-STEP (Adaptable and Seamless Technology transfer Program through target-driven R&D) Grant Number JPMJTM20CF. SMT was kindly provided by Nikko Chemicals Co., Ltd.

---

JOURNAL

Chemistry Letters

DOI

10.1246/cl.220306 

METHOD OF RESEARCH

Experimental study

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Enhancing the Foam Stability of Aqueous Solution with High Ethanol Concentration via Co-Addition of Surfactant, Long-Chain Alcohol, and Inorganic Electrolyte

People who were most physically active fared worse during the pandemic

Timing was everything when it came to dealing with the coronavirus pandemic and exercising

Peer-Reviewed Publication

NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY

When the world shut down in March 2020, many of us scaled back on exercise and other physical activities. Those resulting COVID kilos yielded interest, and many of us still haven’t rid ourselves of them.

But it could have been worse.

It could be that forcing too much physical activity too early in the pandemic was not healthy, either, according to some recent research results.

Physically active people struggled too

Researchers at the Norwegian University of Science and Technology (NTNU) looked at how the mental health of physically active adults progressed during the first phase of the pandemic. Physically active people generally have better mental health than inactive people.

The researchers collected the first data in June 2020, just a few months into the shutdown, and then again six months later. The participants were members of Kondis, a Norwegian organization for fitness sports.

Women’s anxiety symptoms remained stable, but men’s anxiety symptoms increased. Both sexes had several symptoms of depression.

The research findings thus showed that the pandemic was associated with worse mental health for the physically active population as well. People who reduced the amount of exercise they did had the most depression symptoms.

The most active individuals struggled the most mentally

The researchers found something unexpected as well.

Those who increased their amount of exercise early after the shutdown in March also experienced the greatest increase in anxiety and depression symptoms half a year after the pandemic erupted.

“The mental health of physically active people who increased their activity level at just over six months into the pandemic deteriorated more than for people who didn’t start exercising more,” says Audun Havnen, an associate professor at NTNU’s Department of Psychology.

So the individuals who trained more early on in the pandemic fared the worst mentally of the all physically active people.

“In other words, pushing ourselves to do a lot of exercise doesn’t always contribute positively to our mental health,” says Linda Ernstsen, associate professor at NTNU’s Department of Public Health and Nursing.

Certain personality traits?

Despite the study results, the researchers are somewhat cautious about issuing solid conclusions. Indeed, the context could be reversed.

“It could be that people who train above the average amount have some personality traits that make them more vulnerable in terms of mental health,” says Havnen.

A large Swedish study of almost 400,000 participants in the Vasaloppet, the world’s largest cross-country ski race, seems to indicate just that.

The NTNU study results also show that people who reported a reduced amount of exercise at the beginning of the pandemic had the relatively highest level of anxiety and depression symptoms.

At the same time, the entire study sample had a significantly lower incidence of mental illness as compared with the population at large.

Physical activity has big benefits

It is important to note that all the 855 participants in the study were physically active.

The study did not make any comparisons with people who engage in little to no physical activity. Inactive individuals usually fare less well.

“Physically active people generally struggle less with depression and anxiety,” Ernstsen says.

Exercise and other physical activity undoubtedly have many benefits. They support better moods and sleep, and keeping up with all kinds of chores in everyday life. Exercise reduces the risk of many different diseases – and if you still get sick, physical activity can make it easier to recover.

But it appears that there could be a limit, and that pushing our physical envelope doesn’t always feel so good either.

Reference: Havnen Audun, Ernstsen Linda. Does Change in Physical Activity During the Initial Phase of the COVID-19 Pandemic Predict Psychological Symptoms in Physically Active Adults? A Six-Month Longitudinal Study. International Journal of Public Health. Volume 67, 2022. ISSN 1661-8564. DOI 10.3389/ijph.2022.1604528

 

---

JOURNAL

International Journal of Public Health

DOI

10.3389/ijph.2022.1604528 

METHOD OF RESEARCH

Survey

SUBJECT OF RESEARCH

People

ARTICLE TITLE

Does Change in Physical Activity During the Initial Phase of the COVID-19 Pandemic Predict Psychological Symptoms in Physically Active Adults? A Six-Month Longitudinal Study.

COVID radar: Genetic sequencing can help predict severity of next variant

Drexel University computer model could help project severity of next COVID variant.

Peer-Reviewed Publication

DREXEL UNIVERSITY

As public health officials around the world contend with the latest surge of the COVID-19 pandemic, researchers at Drexel University have created a computer model that could help them be better prepared for the next one. Using machine learning algorithms, trained to identify correlations between changes in the genetic sequence of the COVID-19 virus and upticks in transmission, hospitalizations and deaths, the model can provide an early warning about the severity of new variants.

More than two years into the pandemic, scientists and public health officials are doing their best to predict how mutations of the SARS-CoV-2 virus are likely to make it more transmissible, evasive to the immune system and likely to cause severe infections. But collecting and analyzing the genetic data to identify new variants — and linking it to the specific patients who have been sickened by it — is still an arduous process.

Because of this, most public health projections about new “variants of concern” — as the World Health Organization categorizes them — are based on surveillance testing and observation of the regions where they are already spreading.

“The speed with which new variants, like Omicron have made their way around the globe means that by the time public health officials have a good handle on how vulnerable their population might be, the virus has already arrived,” said Bahrad A. Sokhansanj, PhD, an assistant research professor in Drexel’s College of Engineering who led development of the computer model. “We’re trying to give them an early warning system – like advanced weather modeling for meteorologists – so they can quickly predict how dangerous a new variant is likely to be — and prepare accordingly.”

The Drexel model, which was recently published in the journal Computers in Biology and Medicine, is driven by a targeted analysis of the genetic sequence of the virus’s spike protein — the part of the virus that allows it to evade the immune system and infect healthy cells, it is also the part known to have mutated most frequently throughout the pandemic — combined with a mixed effects machine learning analysis of factors such as age, sex and geographic location of COVID patients.

Learning to Find Patterns

The research team used a newly developed machine learning algorithm, called GPBoost, based on methods commonly used by large companies to analyze sales data. Via a textual analysis, the program can quickly home in on the areas of the genetic sequence that are most likely to be linked to changes in the severity of the variant.

It layers these patterns with those that it gleans from a separate perusal of patient metadata (age and sex) and medical outcomes (mild cases, hospitalizations, deaths). The algorithm also accounts for, and attempts to remove, biases due to how different countries collect data. This training process not only allows the program to validate the predictions it has already made about existing variant, but it also prepares the model to make projections when it comes across new mutations in the spike protein. It shows these projections as a range of severity – from mild cases to hospitalizations and deaths – depending on the age, or sex of a patient.

“When we get a sequence, we can make a prediction about risk of severe disease from a variant before labs run experiments with animal models or cell culture, or before enough people get sick that you can collect epidemiological data. In other words, our model is more like an early warning system for emerging variants” Sokhansanj said.

Genetic and patient data from the GISAID database – the largest compendium of information on people who have been infected with the coronavirus – were used to train the algorithm. Once the algorithms were primed the team used them to make projections about the Omicron subvariants post-BA.1 and BA.2.

“We show that future Omicron subvariants are likelier to cause more severe disease,” Sokhansanj said. “Of course, in the real world, that increased disease severity will be mitigated by prior infection by the previous Omicron variants – this factor is also reflected in the modeling.”

Keeping up with Covid

Drexel’s targeted approach to predictive modeling of COVID-19 is a crucial development because the massive amount of genetic sequencing data being collected has strained standard analysis methods to extract useful information quickly enough to keep up with the virus’s new mutations.

“The amount of spike protein mutations has already been quite substantial and it will likely continue because the virus is encountering hosts that have never been infected before,” said Gail Rosen, PhD, a professor in the College of Engineering, who heads Drexel’s Ecological and Evolutionary Signal-processing and Informatics Laboratory.

“Some estimates suggest that SARS-CoV-2 has only ‘explored’ as little as 30-40% of the potential space for spike mutations,” she said. “When you consider that each mutation could impact key virus properties, like virulence and immune evasion, it seems vital to be able to quickly identify these variations and understand what they mean for those who are vulnerable to infection.”

Rosen’s lab has been at the forefront of using algorithms to cut though the noise of genetic sequencing data and identify patterns that are likely to be significant. Early in the pandemic the group was able to track the geographic evolution of new SARS-CoV-2 variants by developing a method for quickly identify and labeling its mutations. Her team has continued to leverage this process to better understand the patterns of the pandemic.

Vision Among Variables

Up until now, scientists have predominantly used genetic sequencing to better identify mutations alongside lab experiments and epidemiological studies. There has been little success in linking specific genetic sequence variations to virality of new variants. The Drexel researchers believe this is due to progressive changes in vaccination and immunity over time, as well as variations in how data is reported in different countries.

“We know that each successive COVID-19 variant thus far has resulted in slightly milder infections because of increases in vaccination, immunity and health care providers having a better understanding of how to treat infections. But what we have discovered through our mixed effects analysis is that this trend does not necessarily hold for each country. This is why our model considers geographic location as one of the variables taken into consideration by the machine learning algorithm,” Sokhansanj said.

While disparities and inconsistencies in patient and public health data have been a challenge for public health officials throughout the pandemic, the Drexel model is able to account for this and explain how it affected the algorithm’s projections.

“One of our key goals was making sure that the model is explainable, that is, we can tell why it's making the predictions that it's making,” Sokhansanj said. “You really want a model that allows you to look under the hood to see, for example, the reasons why its predictions may or may not agree with what biologists understand from lab experiments — to ensure the predictions are built on the right structure.”

A Better View

The team notes that advances like this underscore the need to provide more public health resources to vulnerable areas of the world — not only for treatment and vaccination, but also for collecting public health data, including sequencing emerging variants.

The researchers are currently using the model to more rigorously analyze the current group of emerging variants that will become dominant after Omicron BA.4 and BA.5.

“The virus can and will continue to surprise us,” Sokhansanj said. “We urgently need to expand our global capacity to sequence variants, so that we can analyze the sequences of potentially dangerous variants as soon as they show up — before they become a worldwide problem.”

---

JOURNAL

Computers in Biology and Medicine

DOI

10.1016/j.compbiomed.2022.105969 

METHOD OF RESEARCH

Computational simulation/modeling

SUBJECT OF RESEARCH

Not applicable

ARTICLE TITLE

Predicting COVID-19 disease severity from SARS-CoV-2 spike protein sequence by mixed effects machine learning

ARTICLE PUBLICATION DATE

27-Aug-2022

Three COVID-19 vaccines may provide greater protection from COVID-19 infections than two

Peer-Reviewed Publication

PLOS

 

IMAGE: RESEARCHERS FIND A THIRD COVID-19 VACCINE DOSE OFFERS BETTER PROTECTION THAN TWO. view more 

CREDIT: HAKAN NURAL, UNSPLASH (CC0, HTTPS://CREATIVECOMMONS.ORG/PUBLICDOMAIN/ZERO/1.0/)

Two vaccine doses provide only limited and short-lived protection against SARS-CoV-2 infection with the Omicron variant. A study publishing September 1st in the open-access journal PLOS Medicine by Mie Agermose Gram at Statens Serum Institut, Copenhagen, Denmark and colleagues suggests that a third COVID-19 vaccine dose increased the level and duration of protection against Omicron infection and hospitalization.

Emergence of new SARS-CoV-2 variants may decrease long-term vaccine durability, increasing the risk of infection and hospitalization. However, evidence is limited regarding the vaccine effectiveness of three vaccines over time. In order to estimate the effectiveness of two or three vaccine doses against COVID-19 infection and hospitalization, researchers conducted a nationwide cohort study of all previously uninfected Danish residents aged 12 and older by accessing individual-level data stored in the national Danish Civil Registration System and Danish Vaccination Registry. The researchers then estimated vaccine effectiveness using vaccination status as a time-varying exposure, adjusting for age, sex, geographic location, and comorbidities, before comparing infection and hospitalization rates to unvaccinated individuals.

The researchers found that a third vaccine dose provided greater protection against infection and hospitalization from the Omicron variant than with two vaccines and also that there was less evidence of waning protection. Future studies are needed to better understand the durability of a third vaccine dose after 120 days and evaluate the need for subsequent boosters. One limitation of the study was that the data was non-randomized, so there could be unmeasured differences between the vaccinated and unvaccinated groups.

According to the authors, “Our findings indicate that a third dose is necessary to maintain protection against infection for a longer time and to ensure a high level of protection against COVID-19 hospitalization with the Omicron variant. Continued emergence of new variants and waning vaccine durability require ongoing evaluation of vaccine effectiveness against infection and hospitalization to inform future vaccination strategies”.

Gram adds, “Despite being less effective against infection with Omicron than previous variants, a third mRNA COVID-19 vaccine dose offers better protection against Omicron infection than two doses and protects well against COVID-19 hospitalization.”

#####

In your coverage, please use this URL to provide access to the freely available paper in PLOS Medicine:

http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1003992

Citation: Gram MA, Emborg H-D, Schelde AB, Friis NU, Nielsen KF, Moustsen-Helms IR, et al. (2022) Vaccine effectiveness against SARS-CoV-2 infection or COVID-19 hospitalization with the Alpha, Delta, or Omicron SARS-CoV-2 variant: A nationwide Danish cohort study. PLoS Med 19(9): e1003992. https://doi.org/10.1371/journal.pmed.1003992

Author Countries: Denmark, United Kingdom

Funding: The author(s) received no specific funding for this work.

---

JOURNAL

PLoS Medicine

DOI

10.1371/journal.pmed.1003992 

METHOD OF RESEARCH

Observational study

SUBJECT OF RESEARCH

People

Second Chance for Science Conference with researchers from Ukraine

Prof. Dr. Carmen Bachmann organizes virtual meetings between German and Ukrainian researchers

Meeting Announcement

UNIVERSITÄT LEIPZIG

“We have 160 presentations on the programme. I’m now looking for partners throughout Germany who fit in thematically with the lectures from Ukraine and will ask if they would like to participate,” said Carmen Bachmann. As the chair of business taxation in the Faculty of Economics and Management Science at Leipzig University, she launched the Chance for Science initiative during the Syrian refugee crisis in 2015 and is now using the volunteer platform and her network to support Ukrainian researchers. The conference will cover a range of topics – from artificial intelligence and veterinary medicine to water research and special tax and legal issues in wartime. This year, for the first time, the initiators and financial supporters of the conference will present Chance for Science awards to nine of the presenters, who will each receive €500. Representatives from the sponsoring companies will also be present at the conference and will explore opportunities to partner with researchers from Ukraine.

Given the enthusiastic response to the first Chance for Science conference in April of this year, Bachmann decided to organise a second one. “Even at the beginning of the war, Ukrainian researchers approached me with the request to help them network with German colleagues. In the beginning, I tried to establish contacts one by one. But at some point, the large number of requests made this no longer feasible, and so the idea for the conference was born,” said Bachmann. This first conference resulted in several successful partnerships being established. She reports, for example, on Professor Anastasiya Babintseva from western Ukraine, who has formed a strong scientific partnership with Professor Mario Rüdiger from the University Hospital Dresden. Since the conference, Babintseva has been in close contact with Rüdiger, who is a neonatologist and paediatric intensivist. Rüdiger and the charity fund German Foundation for Sick Newborns (DSKN) have delivered equipment for the treatment of newborns to Ukraine. Joint webinars and training to help Ukrainian doctors and nurses improve their theoretical knowledge and practical skills are also planned.

The conference on 8 and 9 September will provide another networking opportunity, from which new contacts can be established afterwards. In addition, networking via the existing platform is still possible online. And Bachmann does not rule out organising a third Chance for Science conference. But for now, she said, she has her hands full with the September meeting.