Fungal infections are a serious health risk. They can be harmful especially to patients whose immune system is compromised through illness or chemotherapy. A team working at the Technical University of Munich (TUM) has discovered an important mechanism in the body’s defences against fungi. The discovery explains, among other things, why people with certain genetic variations are more susceptible to fungal infections.

To fight pathogens such as viruses, bacteria and fungi, the body has a complex security system. The widespread notion of white blood cells operating as the ‘body police,’ tracking down and incapacitating invaders, falls far short of adequately describing how the immune system actually works. Before the body’s defence response gets started, complex chains of biochemical reactions occur at the molecular level. The scientists studying a certain immune reaction are often not yet aware of all links in these chains.

This is true, for example, in the case of the innate immune response to certain fungi studied by the team under Professor Jürgen Ruland, who holds the chair in Clinical Chemistry and Pathobiochemistry at TUM. It was known that the reaction began with protein elements known as C-type lectin receptors of blood and tissue cells recognizing certain molecules on fungus cells and triggering the chain reaction, also known as a signal pathway. It has also been known for some time that the protein CARD9 plays an important role in this chain. Only when CARD9 is present is it possible for the body to trigger an immune response that destroys the fungus cells.

Jürgen Ruland and his team demonstrated that before CARD9 can perform its role in the chain, molecules known as Vav proteins must be active. Three of these proteins occur in the human body: Vav1, Vav2 and Vav3. If all three are deactivated, the body is particularly susceptible to fungus infections even if CARD9 is present. As signal molecules, the Vav proteins play a role in various processes, including immune responses. ‘Previously, however, the functions of the Vav proteins were understood mainly as part of the acquired or adaptive immune system. Their functions in the innate immune response, which is the focus of our work, remain largely unexplored,’ explains Dr. Susanne Roth, the first author of the study. As the name suggests, the acquired immune response means that the body learns to fight off certain substances only in the course of a person’s life. By contrast, the substances resisted by the innate immune response are genetically determined before birth.

The researchers were also able to use patient data to demonstrate the importance of Vav proteins for innate immunity: A certain genetic variation was disproportionately represented among a group of people suffering from candidiasis, a yeast infection. The variation causes the protein Vav3 to occur in a slightly modified form. It was the absence of Vav3 that had the strongest impact on the immune response in past experiments.

The newly discovered role of the Vav proteins could be used in the future to design diagnostic approaches. ‘It would be conceivable to develop a risk profile for chemotherapy patients,’ says Jürgen Ruland. He suggests that genetic analysis could be used to determine which patients might be more susceptible to fungal infections.

EurekAlert www.eurekalert.org/pub_releases/2016-12/tuom-ieo121916.php

1 000 new mutations in the blood group genes: that is what physician and former programmer Mattias Möller found in his research study in which he developed new software and investigated blood group genes in 2 504 people.

The international project 1000 Genomes is so far the world’s largest mapping of human genetic variants. By creating a new computer program, Mattias Möller processed the genomes of 2 504 people. He imported these genomes to his newly developed database Erythrogene, and matched them against previously known genetic variants. The result was the discovery of 1 000 hitherto unknown mutations which could have a negative effect in the case of blood transfusions, for example.

“Never before has there been a worldwide mapping of blood group genes in healthy individuals. Most previously known blood group variants were discovered when a blood transfusion failed, i.e. when it didn’t work between the donor and the recipient. I started from the genes instead, to find variations in DNA which might give rise to a new antigen, likely to cause problems in case of transfusion, for example”, explains Mattias Möller, doctoral student at the Department of Laboratory Medicine.

On the surface of the red blood cells are proteins and sugar molecules, in which small differences give rise to different antigens. The ability to identify and match blood group types is important for blood transfusions, but also in pregnancy and before certain types of transplantation. A transfusion with mismatched blood can lead to a transfusion reaction. This type of reaction can be mild and barely noticeable, or so strong that the blood cells rupture and, in the worst cases, the patient dies.

Mattias Möller’s study showed that 89 per cent of the genetic variants were previously known, but among the remaining 11 per cent were a total of 1 000 different mutations which were absent from official catalogues of known blood group variants.

“Of course not all variants lead to new antigens. But we need to go on and conduct further analyses to investigate how the genetic expression changes, i.e. how the molecules on the surface of the cell are affected.ˮ

There are currently 352 mapped antigens, but the research has so far mainly focused on populations in Europe and North America. A future research field is Africa, where there is greater variation between different population groups. As research on African populations increases, in combination with blood transfusions becoming more common there, many new antigens are likely to be discovered.

Lund Universitywww.lunduniversity.lu.se/article/how-1-000-new-genetic-variants-were-discovered-in-blood-groups

Engineers at the University of California San Diego have developed a desktop diagnosis tool that detects the presence of harmful bacteria in a blood sample in a matter of hours instead of days.  The breakthrough was made possible by a combination of proprietary chemistry, innovative electrical engineering and high-end imaging and analysis techniques powered by machine learning.  

To identify low levels of harmful bacteria among a large number of human blood cells, researchers for the first time melted bacterial DNA in 20,000 extremely small simultaneous reactions. Each reaction contained only 20 picoliters—a scale that is hard to picture: one drop of rain contains hundreds of thousands of picoliters.

Each type of DNA has a specific signature as it comes apart during melting. As the melting process is imaged and analysed, researchers can use machine learning to determine which types of DNA appear in blood samples. During experiments, the system accurately identified, 99 percent of the time, DNA sequences from bacteria causing food-borne illnesses and pneumonia—in less than four hours.  

“Analysing this many reactions at the same time at this small a scale had never been attempted before,” said Stephanie Fraley, a professor of bioengineering at the Jacobs School of Engineering at UC San Diego and the paper’s lead author. “Most molecular tests look at DNA on a much larger scale and look for just one type of bacteria at a time. We analyse all the bacteria in a sample. This is a much more holistic approach.”

Current methods used to detect and identify bacteria rely on cultures, which can take days. That is too long to provide physicians with an effective and timely diagnosis tool—as anyone who has been prescribed antibiotics while waiting for test results knows.

It all starts with one milliliter of blood, which researchers inoculated with Listeria monocytogenes, a food-borne bacterium that causes about 260 deaths a year in the United States, and Streptococcus pneumoniae, which causes everything from sinus infections, to pneumonia, to meningitis.

Researchers isolated all DNA from the blood sample. The DNA was then placed on a digital chip that allowed each piece to independently multiply in its own small reaction. For the process to work at such small scales—each well containing DNA in the chip was only 20 picoliters in volume—researchers used a proprietary mix of chemicals subject to a provisional patent.

The chip with the amplified DNA was placed in an innovative high-throughput microscope that Fraley and her team designed. The DNA was then heated in increments of 0.2 degrees Celsius, causing it to melt at temperatures between 50 to 90 degrees Celsius –about 120 to 190 degrees Fahrenheit.

As the DNA double-helix melts, the bonds holding together the DNA strands break. Depending on the DNA’s sequence, the bonds have different strengths and that changes the way the strands unwind from each other. This creates a unique sequence-dependent fingerprint, which researchers can detect using a special dye. The dye causes the unwinding process to give off fluorescent light, creating what researchers call a melting curve—a unique signature for each type of bacteria.

When engineers imaged the melting process with the high-throughput microscope, they were able to capture the bacteria’s melting curves. They then analysed the curves with a machine learning algorithm they developed.

In previous work, the algorithm was trained on 37 different types of bacteria undergoing different reactions in different conditions. The researchers showed that it was able to identify bacteria strains with 99 percent accuracy.

University of California – San Diegoucsdnews.ucsd.edu/pressrelease/new_method_to_identify_bacteria_in_blood_samples_works_in_hours_instead_of

Each year, about 1.38 million women worldwide are diagnosed with breast cancer. Advances in diagnosis and treatment have facilitated a 90-percent, five-year survival rate, among those treated. However, with the increased rate and length of survival following breast cancer, patients face a lifetime risk of developing lymphedema, one of the most distressing and feared late onset breast cancer-related effects.

Lymphedema is an abnormal accumulation of lymph fluid in the ipsilateral body area, or upper limb. This remains an on-going major health problem affecting more than 40 percent of 3.1 million breast cancer survivors in the U.S. Lymphedema following breast cancer surgery is typically considered to be primarily due to the mechanical injury from surgery. However, recent research has found that inflammation-infection and higher body mass index are also main predictors of lymphedema.

Researchers from New York University Rory Meyers College of Nursing (NYU Meyers), led by Dr. Mei R. Fu, PhD, RN, FAAN, conducted a study, “Precision assessment of heterogeneity of lymphedema phenotype, genotypes and risk prediction,” to address this phenomenon and prospectively examine phenotype of arm lymphedema by limb volume and lymphedema symptoms in relation to inflammatory genes in women treated for breast cancer.

The study is the first of its kind in exploring associations between genetic susceptibility targeting identified phenotypic risk factors of inflammation and heterogeneous phenotypes of lymphedema.

“It remains puzzling that up to 23% of survivors who only had lumpectomy with sentinel lymph node biopsy of 1 or 2 lymph nodes removed have developed lymphedema, while some survivors who had mastectomy with more than 10 lymph nodes removed have not,” said Dr. Fu. “There is a critical need to understand heterogeneity of lymphedema phenotype in relation to assessment of lymphedema phenotype and related biological mechanism.”

The study consisted of 136 women with a mean age of 52 with a first time diagnosis of breast cancer (Stage I-III), and were scheduled for surgical treatment of lumpectomy or mastectomy. The researchers measured data at 4-8 weeks post-surgery and 12 months post-surgery to monitor development of lymphedema during this period. They used lymphedema phenotyping to measure more symptoms than the typical method of observing swelling and limb volume. The symptom phenotyping was important in indicating early stage lymphedema where limb volume cannot be assessed yet.

The researchers found that using symptom phenotyping, prior to surgery, only one participant had more than 8 symptoms and only 18 had 1-7 symptoms. At 4-8 weeks post-surgery all participants had at least one symptom, 53% had 1-7 symptoms, and 46% had more than 8 symptoms, whereas only 16% had arm lymphedema defined by limb volume increase. At 12 months post-surgery 26.5% had more than 8 symptoms and 63% reported 1-7 symptoms, whereas only 22.8% had arm lymphedema as defined by limb volume.
Additionally, prior to surgery, identification of symptom phenotypes was not feasible, as 86% of participants were symptom-free. However, at 4-8 weeks post-surgery 58.1% of participants were classified as the phenotype of impaired limb mobility, with 86% discomfort, and 55.9% fluid accumulation. At 12 months 55.2% of participants were classified as the phenotype of impaired limb mobility with 38.2% pain/discomfort, and 44.1% fluid accumulation.

This data found significant associations between genotypes related to several lymphatic and inflammatory genes and symptom phenotypes of impaired limb mobility, fluid accumulation, and pain/discomfort. The data further provides support for heterogeneity of lymphedema phenotypes, especially phenotype of symptom clusters based on biological mechanisms.

Dr. Fu notes that the sample size and only 12-month period of observation does put limitations on the study.

New York Universitywww.nyu.edu/about/news-publications/news/2017/february/nyu-researchers-study-patients-genetic-and-susceptibility-risk-f.html

Casting one of the largest genomic nets to date for the rare tumours of the autonomic nervous system known as pheochromocytoma and paraganglioma (PCC/PGL) captured several new mutations driving the disease that could serve as potential drug targets, researchers from Penn Medicine and other institutions report.

Analysing genetic data of 173 patients from The Cancer Genome Atlas, researchers, including senior author Katherine Nathanson, MD, a professor in the division of Translational Medicine and Human Genetics at the Perelman School of Medicine at the University of Pennsylvania and associate director for Population Science at Penn’s Abramson Cancer Center, identified CSDE1 and fusion genes in MAML3 as drivers of the disease, both a first for any cancer type. The researchers also classified PCC/PGL into four distinct subtypes, each driven by mutations in distinct biological pathways, two of which are novel.
“What’s interesting about these tumours is that while they are astonishingly diverse genetically, with both inherited and somatic drivers influencing tumorigenesis, each has a single driver mutation, not multiple mutations,” Nathanson said. “This characteristic makes these tumours ideal candidates for targeted therapy.”  Other cancer types typically contain anywhere from two to eight of these driver mutations.

The discovery of these single drivers in PCC/PGL provides more opportunities for molecular diagnosis and prognosis in these patients, particularly those with more aggressive cancers, the authors said.

PGLs are rare tumours of nerve ganglia in the body, whereas PCCs form in the centre of the adrenal gland, which is responsible for producing adrenaline. The tumour causes the glands to overproduce adrenaline, leading to elevated blood pressure, severe headaches, and heart palpitations.  Both are found in about two out of every million people each year. An even smaller percentage of those tumours become malignant – and become very aggressive. For that group, the five-year survival rate is about 50 percent.

Matthew D. Wilkerson, MD, the Bioinformatics Director at the Collaborative Health Initiative Research Program at the Uniformed Services University, is the paper’s co-senior author.

To identify and characterize the genetic missteps, researchers analysed tumour specimens using whole-exome sequencing, mRNA and microRNA sequencing, DNA-methylation arrays, and reverse-phase protein arrays.  The four molecularly defined subgroups included: a kinase-signalling subtype, a pseudohypoxia subtype, a cortical admixture subtype, and a Wnt-altered subtype.  The last two have been newly classified.

The results also provided clinically actionable information by confirming and identifying several molecular markers associated with an increased risk of aggressive and metastatic disease, including germline mutations in SDBH, somatic mutations in ATRX (previously established in a Penn Medicine study), and new gene fusions – a genetic hybrid, of sorts – in MAML3.

Because the MAML3 fusion gene activates the Wnt-altered subtype, the authors said, existing targeted therapies that inhibit the beta-catenin and STAT3 pathways may also prove effective in certain PCC/PGL tumours.

Penn Medicine www.pennmedicine.org/news/news-releases/2017/february/in-depth-gene-search-reveals-new-mutations-drug-targets-in-rare-adrenal-tumors