Phages are key to emergence of “superbugs” and their treatment
The researchers showed that, contrary to a dominant theory in the field of evolutionary microbiology, the process of adaptation and diversification in bacterial colonies doesn’t start from a homogeneous clonal population. They were shocked to discover that the cause of much of the early adaptation wasn’t random point mutations. Instead, they found that phages, which we normally think of as bacterial parasites, are what gave the winning strains the evolutionary advantage early on.
“Essentially, a parasite became a weapon,” said senior author Vaughn Cooper, PhD, Professor of Microbiology and Molecular Genetics at Pitt. “What killed off more sensitive bugs gave the advantage to others.”
When it comes to bacteria, a careful observer can track evolution in the span of a few days. Because of how quickly bacteria grow, it only takes days for bacterial strains to acquire new traits or develop resistance to antimicrobial drugs.
The new study shows that bacterial and phage evolution often go hand in hand, especially in the early stages of bacterial infection. This is a multilayered process in which phages and bacteria are joined in a chaotic dance, constantly interacting and co-evolving.
When the scientists tracked changes in genetic sequences of six bacterial strains in a skin wound infection in pigs, they found that jumping of phages from one bacterial host to another was rampant — even clones that didn’t gain an evolutionary advantage had phages incorporated in their genomes. Most clones had more than one phage integrated in their genetic material — often there were two, three or even four phages in one bug.
Funding for HIV latency research using single cell analysis
The National Institute on Drug Abuse, part of the National Institues of Health (NIH), is funding the Browne lab in the UNC HIV Cure Center for a study on the effects of cannabis use on the reservoir of HIV that is dormant within patients but becomes activated and spreads when antiretroviral medications are ceased. This phenomenon is called HIV latency, and it’s considered the main barrier to eradicating the virus that causes AIDS.
UNC HIV Cure Center researcher Ed Browne, PhD, Assistant Professor in the UNC Department of Medicine, is the principal investigator of the $4-million, 5-year research project.
Increasing evidence suggests that drugs of abuse, such as the cannabis (or marijuana), affect the size and nature of the virus reservoir. Cannabis activates the CB2 receptors that are widely expressed on the surface of immune cells, including the CD4 T cells.
“Our hypothesis is that cannabis exposure during HIV infection alters the size, location, and genetic characteristics of the latent HIV reservoir through the activation of CB2-dependent cell signaling in CD4 T cells,” Browne said.
The UNC Cure Center research team will use cutting-edge methods from the fields of single cell multi-omic analysis to characterize cannabis effects on the latent HIV reservoir.
First, the researchers will capitalize on a primary CD4 T cell model of HIV latency developed in the Browne lab to investigate how CB-induced signaling impacts viral/host gene expression and chromatin structure in latently infected cells.
Second, they will use a newly developed single cell experimental assay to determine the impact of cannabis use on the size and location of the intact HIV reservoir, analyzing samples from a cohort of cannabis-using individuals with HIV.
Third, they will extend their findings to conduct a detailed genomic analysis of the impact of cannabis use on cellular and viral gene expression in people with HIV. Specifically, the researchers will analyze blood cells and CD4 T cells from cannabis-using individuals, using single cell RNA sequencing technologies, and compare what they find to non cannabis-using individuals with HIV. The researchers will identify any cellular and genetic signatures that distinguish cannabis-using people with HIV from non-using HIV-positive individuals.
Johns Hopkins method outperforms previous assessments for risk in cardiac sarcoidosis
Johns Hopkins University scientists have developed a new tool for predicting which patients suffering from a complex inflammatory heart disease are at risk of sudden cardiac arrest. Published in Science Advances, their method is the first to combine models of patients’ hearts built from multiple images with the power of machine learning.
“This robust new personalized technology outperformed clinical metrics in forecasting future arrhythmia and could transform the management of cardiac sarcoidosis patients,” said senior author Natalia Trayanova, Professor of Biomedical Engineering and Co-Director of the Alliance for Cardiovascular Diagnostic and Treatment Innovation (ADVANCE) at Johns Hopkins.
Doctors don’t currently have precise methods for assessing which patients with cardiac sarcoidosis, a condition causing inflammation and scarring that can trigger irregular heartbeats, are likely to have a fatal arrthmia; meaning that some patients don’t survive, while others undergo unnecessary, invasive interventions. A recent meta-analysis cited in the study found that roughly only one third of CS patients receive adequate treatment.
Trayanova, who is also a professor at the Johns Hopkins School of Medicine, said, “Some CS patients perish, often in the prime of their life, while others have a defibrillator implanted unnecessarily and often deal with the complications, including infections, device malfunction, and inappropriate shocks, without receiving any real benefit.”
In their study, the researchers created digital three-dimensional models of the hearts of 45 CS patients treated at the Johns Hopkins Hospital. To do this, they took the novel approach of combining data from two different kinds of heart scans: contrast-enhanced cardiac MRIs, which detect fibrosis, or scarring, and PET scans, which detect inflammation. The team used computer simulations to apply a series of electrical signals at various locations throughout each of the models and gathered millions of data points measuring each heart’s reaction.
The tool significantly outperformed standard clinical metrics for predicting cardiac arrest in CS patients.
Lastly, the team compared their simulations against scans of lesions in the hearts of the patients who had subsequently undergone a procedure to reset their heartbeats, finding that their predictions were consistent with actual outcomes.
Hard working enzyme keeps immune cells in line
Researchers at La Jolla Institute for Immunology (LJI) have shed light on a process in immune cells that may explain why some people develop cardiovascular diseases, according to a news release from the organization.
Their research, published recently in Genome Biology, shows the key role that TET enzymes play in keeping immune cells on a healthy track as they mature. The scientists found that other enzymes do play a role in this process — but TET enzymes do the heavy lifting.
TET enzymes control gene expression by triggering a process called demethylation, where a molecule called a methyl group is removed from where it sits in the genetic code. Demethylation is important because it alters how a cell “reads” DNA.
For the study, the researchers investigated how immune cell DNA can be altered by either TET enzymes (a process called passive demethylation) or by a DNA repair enzyme called TDG (active demethylation).
The researchers aimed to uncover which demethylation pathway has a bigger role in determining the gene expression of immune cells.
The researchers started with two immune cell models: CD4 “helper” T cells and monocytes. Both cell types must proliferate and mature into more specific cell types to help fight off pathogens. However, once monocytes are differentiated into macrophages and stimulated with a molecule called LPS, they stop proliferating. By taking a close look at these CD4 helper T cells and macrophages the researchers could better understand proliferating and non-proliferating models.
The proliferation process is very quick, making it a prime time to witness how demethylation occurs and how it affects gene expression. Onodera used CD4 helper T cells to analyze the demethylation process using a cutting-edge computational analysis program developed for this study. This tool gives scientists a look at which regions of DNA within a cell are methylated.
Using a new technique called pyridine borane sequencing, the researchers showed that “active” demethylation — through TDG — is working in immune cells. Onodera says TDG’s role is minor: it does the job of removing two molecules generated by TET enzyme activity.
NIH panel proposes standard definition of placental SARS-CoV-2 infection
A panel of experts convened by the National Institutes of Health (NIH) has recommended standardized criteria to define infection of the placenta with SARS-CoV-2, the virus that causes COVID-19. The panel also released a guidance about the best methods to evaluate placental SARS-CoV-2 infections for research and clinical applications.
SARS-CoV-2 infection during pregnancy has been linked to complications that may involve or be reflected in the placenta, including preeclampsia and preterm birth. To date, researchers have used a variety of methods to diagnose SARS-CoV-2 infection of the placenta, making it difficult to compare results from different studies and to establish definitive scientific evidence about the risks of placental infection.
To address these gaps, NIH’s Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) virtually convened a group of experts in obstetrics, virology, placental pathology, infectious disease, immunology and molecular biology to propose a standardized definition of placental infection. The resulting guidance appears in the American Journal of Obstetrics and Gynecology.
The experts recommend preferred techniques to detect SARS-CoV-2 replication, viral transcripts or proteins in placental tissue. Depending on the scientific rigor of the technique used, the likelihood of placental SARS-CoV-2 infection may be classified as definitive, probable, possible or unlikely. The authors encourage investigators to use the most scientifically rigorous technique available in their laboratory or clinic. They also recommend that scientific papers reporting placental SARS-CoV-2 infection describe the location and number of placental tissue samples collected, method of preserving the tissue and detection technique. Finally, they offer guidance for handling, processing and examining placental tissue. The authors anticipate that use of these recommendations will make it easier to compare and interpret results across studies.
