The fungal puppet master has been living a secret life
The post The Bizarre Life Cycle of “Zombie-Ant” Fungus Gets a New Twist appeared first on Nautilus.
Have you ever wondered how researchers use artificial intelligence (AI) in environmental science? Certain AI computer models can learn from scientific data and operate without manual programming, in a process called machine learning. Machine learning models can identify patterns in environmental datasets and help scientists assess public health risks linked to environmental conditions.
One well-known public health risk is the rise in antibiotic-resistant bacteria. These bacteria carry genes called antibiotic resistance genes that protect them from antibiotic medicines. As the number of these genes increases, the medicines become less effective, and diseases spread faster.
Agricultural soils are the largest reservoirs of antibiotic resistance genes, because manure from livestock like cows and pigs often contains leftover antibiotics fed to them. When used as fertilizer, this manure transfers antibiotics into the agricultural soil, where bacteria develop antibiotic resistance genes.
To better understand how antibiotic-resistant bacteria will affect global health in the future, scientists want to develop faster ways to detect antibiotic resistance genes. However, current methods of detection are slow and fail to predict future trends. To address this problem, a group of scientists from Algeria used machine learning models to predict the prevalence of antibiotic resistance genes in soil microbes under future climate scenarios, and to identify the key environmental drivers and high-risk areas.
The team compiled existing microbial data from 3 public databases: the National Center for Biotechnology Information’s Sequence Read Archive, the Metagenomic Rapid Annotations using Subsystems Technology database, and the Joint Genome Institute’s Integrated Microbial Genomes & Microbiomes database. Their final dataset contained about 2,000 agricultural soil samples from 67 countries across 6 continents. These samples represented a wide range of soil characteristics, climate conditions, and different types of antibiotic resistance genes.
They integrated the microbial dataset with climate data, including global temperature and precipitation measurements from WorldClim, and land use data, including crop types, irrigation systems, and livestock density from the European Space Agency Climate Change Initiative Land Cover maps. The researchers also included data on future climate projections for 2050 and 2070 from the World Climate Research Programme based on low, medium, and high global greenhouse gas emission scenarios.
After preparing the datasets, the team set up 6 machine learning models that differ in terms of their data size, model complexity, analytical speed, and customization. These models included Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), Support Vector Machine (SVM), Deep Neural Network (DNN), and Logistic Regression (LR).
They ran each model using different combinations of variables from their datasets, including soil properties, microbial community metrics, climate variables, and land use characteristics. To validate the models, the team separated the full dataset into 10 random subsets. They trained the models on 9 of the subsets, then recorded the result of the 10th subset. Each model repeated this process 10 times in a different order so that each subset was evaluated once in the results, using a technique known as stratified 10-fold cross-validation. The researchers scored each model on 5 performance metrics, including precision, sensitivity, and predictive power. Based on these results, they determined that LightGBM was the most accurate model.
They found that the LightGBM model identified soil temperature as the strongest environmental predictor of antibiotic resistance genes. At soil temperatures above 18°C (about 64°F), the number of antibiotic resistance genes increased dramatically. The model also identified soil acidity, organic carbon content, moisture, and annual precipitation as influential variables, accounting for 71% of the increase in antibiotic resistance genes under future climate scenarios. Likewise, the LightGBM model predicted that the number of high-risk areas would increase by 35% under the high-emissions scenario, with South Asia, Sub-Saharan Africa, and Mediterranean Europe as the most vulnerable regions.
Based on the LightGBM model output, the team concluded that soil conditions will change to favor antibiotic resistance genes under all future climate scenarios. They also suggested that LightGBM is a fast and effective model for environmental predictions that could be used to assess other climate change risks such as natural disasters. They recommended that future researchers explore how to apply machine learning methods to early warning systems and utilize machine learning results in environmental management decisions.
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It hijacks a common process present in all cells
The post How This Emerging Tick-borne Virus Escapes Your Immune System appeared first on Nautilus.
Nitrogen is an essential building block of proteins, amino acids, and DNA. Without nitrogen, cells can’t function or reproduce. Nitrogen is abundant in the atmosphere as dinitrogen gas, but plants and animals can’t access atmospheric nitrogen. Instead, we rely on biologically available forms like ammonia and nitrate.
Specialized microbes can transform atmospheric nitrogen into ammonia via a process called biological nitrogen fixation. Nitrogen-fixing soil bacteria have a unique protein complex, the nitrogenase complex, that facilitates this nitrogen transformation. The nitrogenase complex is activated by a group of genes known as nif genes.
Legume plants like peanuts, peas, and beans have nitrogen-fixing bacteria in the soil zone around their roots, called the rhizosphere. The symbiotic relationship between nitrogen-fixing soil bacteria and legume plants supplies most of the biologically available nitrogen to life on Earth.
Bacteria attached to plant roots “feed” nitrogen to plants through the soil, and in turn receive organic acids for energy from plants performing photosynthesis. Source: Wikimedia Commons
However, one piece of the puzzle remains unexplored: the role of soil viruses in these nitrogen transformations, referred to as the nitrogen cycle. Viruses are microscopic particles made up of genetic material and proteins, but they can’t reproduce without a host cell. Scientists consider viruses to be biological entities that are halfway between living and non-living.
To reproduce, viruses contact a host cell and inject their genetic material into it. The virus’s genetic material takes over the host cell’s genome and forces the cell to produce proteins that assemble into new viruses. As new viruses are created, they can incorporate genes from the host cell into their own genetic material. Genes that are transferred from a host cell to a virus are known as auxiliary metabolic genes (AMGs). Viruses can carry AMGs and pass them to other hosts or use them to increase their own ecological fitness.
Scientists from China, Spain, and the Czech Republic set out to investigate whether viruses from legume roots could increase local soil nitrogen fixation by expressing nif AMGs or by transferring nif genes to other bacteria. First, they determined the global distribution of viral nitrogen-fixing genes by analyzing about 8.6 million viral genomes from the Integrated Microbial Genomes/Virus database. They looked for the DNA sequences of known nitrogen-fixing genes and the locations where the viruses were sampled. They found that only 0.003% of the viruses in the database had at least 1 nitrogen-fixing gene, but they clustered in the same locations as nitrogen-fixing bacteria.
The team also found 3 types of viruses that most commonly carried nitrogen-fixing genes: Kyanoviridae, Nudiviridae, and Bronfenbrennervirinae. Kyanoviridae viruses carried a nif gene called nifU. The researchers used a computer program called DRAM-v to confirm that nifU was a fully functional gene and a real tool that viruses could use.
Next, the team collected soil samples from a cowpea field in Nanjing, China, to test whether the cowpea roots influenced the abundance of viruses using nitrogen-fixing genes. They collected soil from the cowpea rhizospheres and soil away from the plants. They analyzed both viral and bacterial RNA in the soil samples to identify active genes, using a sequencing process called metatranscriptomics. They found that the viral nifU gene was actively expressed in the cowpea rhizosphere samples more than in the non-crop soil. Although about 96% of nifU genes were being expressed by bacteria, viruses contributed about 4%.
The researchers then assessed whether rhizospheric viruses changed the amount of nitrogen being fixed in these soils. They set up small, enclosed containers of sterile soil and added either bacteria or a mixture of bacteria and viruses extracted from the cowpea rhizospheres. They found that soil with viruses had higher total nitrogen (36 milligrams per kilogram, or mg/kg) than soil without viruses (17 mg/kg).
Finally, they adjusted the air in each container to have a different form of dinitrogen gas. Atoms of the same element that have different atomic masses are known as isotopes. Nitrogen has 2 stable isotopes: lighter nitrogen-14 and heavier nitrogen-15. Bacteria or viruses that fix nitrogen at natural isotope abundances will take up nitrogen-14. But scientists can track who in the population fixes nitrogen by adding nitrogen-15 to the air, a process called nitrogen-15 stable isotope probing. Nitrogen-fixers will incorporate the heavy nitrogen-15 into their biomass over time and increase their weight, allowing researchers to separate and identify them.
The team grew the bacteria and viruses with nitrogen-15 for 35 days, then used stable isotope probing to separate the nitrogen fixers. They detected viral nifU AMGs among the heavier biomass, confirming that rhizospheric viruses were fixing nitrogen.
The team concluded that rhizospheric viruses and the viral nifU AMG can increase nitrogen fixation in cowpea soils. The team suggested that although viruses with nitrogen-fixing genes are rare, they can influence the soil nitrogen cycle. They recommended that future researchers further test the contribution of viral nifU genes to plant nitrogen fixation with controlled infection experiments.
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They could complicate the hunt for extraterrestrial life—and compromise astronaut health
The post All the Microbes That Could Survive in Space appeared first on Nautilus.
Scientists have uncovered a shared target used by multiple diarrhea-causing bacteria to invade the gut. Despite decades of research, scientists still do not have vaccines against two of the world’s most common causes of severe bacterial diarrhea: enterotoxigenic E. coli (ETEC) and Shigella. Together, these pathogens infect hundreds of millions of people each year and [...]A new study suggests that altering the gut microbiome with probiotics may provide additional benefits for older adults being treated for depression. Could a daily probiotic help ease depression in older adults? A new clinical trial suggests the answer may be yes, adding to growing evidence that the gut and brain are more connected than [...]In a groundbreaking advance at the intersection of bioengineering and microbiology, researchers at Harvard’s John A. Paulson School of Engineering and Applied Sciences have unveiled a pioneering device known as a pico-calorimeter. This remarkable instrument is capable of directly detecting heat signals emanating from minute populations of living cells, a feat that until now has remained technologically elusive due to the vanishingly small scale of these thermal signatures. By enabling real-time metabolic tracking at unprecedented sensitivity, the pico-calorimeter promises to revolutionize our understanding and monitoring of cellular activity, bacterial growth, and antibiotic response.
At the core of this innovation is the principle that living cells, as they metabolize nutrients, grow, divide, and react to external stimuli such as drugs, intrinsically emit heat. This metabolic heat, although incredibly subtle, offers a direct, unmediated insight into the physiological state of cells. Unlike conventional methods that infer cellular metabolism indirectly through oxygen consumption or chemical byproducts, the pico-calorimeter provides a direct calorimetric measurement, offering a more immediate and accurate assay of cellular energetics.
The technical architecture of the device is a marvel of microengineering. It consists of three ultrafine glass capillaries aligned on a delicately micromachined membrane with near-atomic precision. One of these capillaries harbors the biological sample suspended in a liquid growth medium, while the remaining two serve as thermodynamic reference points. As the bacteria or other cells within the sample metabolize and proliferate, they release minute quantities of heat. This thermal flux generates infinitesimal temperature gradients relative to the reference capillaries, which are then transduced into electrical signals by a nearby thermopile—an exquisitely sensitive heat-to-electricity converter capable of resolving fluctuations on the order of picowatts.
A critical enhancement in this iteration of the pico-calorimeter lies in its housing within a vacuum chamber. This vacuum environment thermally isolates the sensor assembly from ambient thermal noise, dramatically amplifying sensitivity by nearly an order of magnitude compared to antecedent designs. The prior versions employed liquid droplets on suspended membranes, which, while innovative, presented operational challenges and limited sensitivity. The current vacuum-sealed, microfluidic integration advances robustness, usability, and measurement fidelity, marking a milestone in the delicate art of thermal detection at the cellular scale.
Demonstrating the device’s prowess, the research team employed the pico-calorimeter to monitor Escherichia coli growth dynamics, beginning with an initial seed population as modest as thirty to forty individual bacterial cells. This capability to detect and analyze such small biological communities unveils immense potential for applications ranging from fundamental microbiology to clinical diagnostics. Notably, the device was employed to examine bacterial metabolic responses upon introduction of antibiotics with varying mechanisms of action—chloramphenicol, rifampicin, and ampicillin—capturing differential heat signatures indicative of altered cellular viability and activity.
These direct calorimetric measurements have revealed metabolic perturbations well in advance of what traditional culture-based microbiological assays could discern. This capability is particularly transformative in clinical scenarios such as sepsis, where detecting and characterizing bacterial populations at extremely low concentrations in blood is vital but presently time-consuming. The pico-calorimeter’s sensitivity could drastically truncate diagnostic timelines from days to hours, allowing more timely and targeted antimicrobial interventions.
Beyond measuring growth and antibiotic susceptibility, the pico-calorimeter enables continuous, real-time monitoring of fundamental cellular parameters including viability, proliferation rate, and stress responses. This temporal resolution offers researchers the invaluable ability to dynamically track cellular states and transitions, capturing metabolic shifts as cells respond to environmental perturbations or pharmacological treatments. Such insights may open new frontiers in cell biology, pharmacodynamics, and personalized medicine.
This breakthrough device represents the culmination of roughly two decades of meticulous research in the Vlassak laboratory, with contributions building from initial exploration of nano-calorimetry techniques aimed at materials science phenomena such as phase transitions in shape memory alloys and metallic glasses. The interdisciplinary bridge extended to biological systems has ushered in ultrasensitive calorimetry methods capable of assessing metabolic heat production in large cells and complex embryonic development processes, laying foundational expertise for this current bio-calorimetric leap.
Technologically, the fabrication of the pico-calorimeter draws upon state-of-the-art micro- and nanofabrication facilities, including the Harvard Center for Nanoscale Systems. The integration of microfluidics and micromachined sensing elements within thermally isolated environments exemplifies the cutting-edge convergence of materials science, electrical engineering, and biological instrumentation. The multidisciplinary synergy underscores the technological sophistication essential for detecting thermal signals billions of times smaller than everyday heat fluxes.
Commercially, the Harvard Technology Development office has filed multiple patents covering the pico-calorimeter and its applications in antimicrobial susceptibility testing. Juanjuan Zheng, a pivotal figure in this research and founder of an innovative startup, is leveraging the technology to deliver practical, label-free, real-time metabolic readouts. These tools hold promise for broad adoption in life sciences research, pharmaceutical development, and clinical diagnostics, harnessing the power of heat measurement to glean functional insights from minute biological samples.
As the research community embraces this transformative platform, interest has surged from a diverse array of scientific domains. The ability to capture direct metabolic information from tiny, dynamic living systems resolves a long-standing challenge in single-cell and small-population analysis. This heralds a new era where functional metabolic data provides early and actionable information on biological states, ranging from cellular growth and stress response to drug efficacy and resistance patterns.
In essence, the Harvard pico-calorimeter transcends conventional bioanalytical tools by transforming infinitesimal heat emissions into a vivid metabolic narrative. This technological breakthrough not only augments our scientific toolkit but also possesses the potential to accelerate biomedical discovery, enhance therapeutic precision, and ultimately improve patient outcomes by enabling rapid, noninvasive interrogation of cellular function. The implications for healthcare, research, and biotechnology are profound, heralding an exciting frontier where the subtle warmth of life becomes an unequivocal signal of cellular health and response.
Subject of Research: Cells
Article Title: A pico-calorimeter for cellular metabolism and antimicrobial susceptibility testing
References: Proceedings of the National Academy of Sciences
Image Credits: Vlassak Group / Harvard SEAS
Keywords: Calorimetry, Chemical analysis, Life sciences, Biophysics, Single cell profiling, Single molecule analysis, Materials science, Physics, Applied sciences and engineering, Applied physics, Engineering, Electrical engineering, Chemical engineering, Mechanical engineering, Health and medicine, Biomedical engineering
As our world is rapidly reshaped by climate change, glaciers have retreated and revealed new swaths of bare land. Throughout the coming decades to centuries, this rocky ground will become dappled with lichens and scrub, eventually giving rise to newborn forests in a process known as ecological succession.
Ecologists have mapped out the stages of ecological succession for plant communities, observing which species are the first to colonize land and how these pioneer species promote secondary growth. Yet before any plants sink their roots into the soil, it is populated by thriving communities of single-celled microbes that prepare it for further habitation. Scientists study how these microbial communities arise to understand how healthy ecosystems develop.
Newly exposed land is nutrient-poor and subject to large temperature fluctuations, so the first species to settle there must overcome these challenges. Pioneer plant species are often habitat generalists, meaning they can thrive under a variety of environmental conditions. However, all plants convert water and sunlight into carbon and energy. Microbes can use many different energy sources, and often contain genes for multiple metabolisms in their genomes. Therefore, researchers wondered whether pioneer microbes could also be defined by their metabolic flexibility.
A team of scientists based at Monash University in Australia tested this hypothesis by studying land left in the wake of 2 retreating glaciers: one on an island off the coast of Antarctica and one in the Swiss Alps. The researchers sampled soils along a path from the tip of the glacier outward, which had been exposed to the air for different amounts of time. By comparing the microbial communities within these soils, the researchers could track the different stages of ecological succession after glacial retreat.
The researchers extracted DNA from the soils and analyzed it using 2 sequencing methods. First, they sequenced a gene called 16S rRNA, which is like a microbial fingerprint for the different species present. They used this method to understand the diversity of these communities and track their species overlap, helping them to identify habitat generalists that thrived under different soil conditions.
To understand the metabolic flexibility of these microbes, the researchers used a second method, known as metagenomics, which sequences all of the DNA in a sample rather than just a single gene. They used these data to reconstruct the entire genomes of microbes present in the soils, providing information on what kinds of metabolic activities they were capable of. The team also measured chemicals like ammonium and sulfide in the soils, as well as atmospheric gases like methane and carbon monoxide, to assess how the microbes used these compounds for growth.
The researchers found microbes inhabiting even the youngest soils, demonstrating the speed at which life takes hold in new environments. The abundance of microbes increased by approximately 8-fold in older soils, alongside a similar rise in species diversity, indicating that complex communities persisted over time. They also found the metabolic capabilities of microbes inhabiting Antarctic and Swiss glacial soils to be remarkably similar, suggesting common selective pressures drove the establishment of these new ecosystems.
They were surprised to discover that the most abundant microbes in younger soils were habitat specialists that were rare in older soils. These pioneer microbes, while still metabolically flexible, had adapted to utilize meager energy sources like atmospheric trace gases, including hydrogen, methane, and carbon monoxide. Many of these microbes could also derive energy from chemicals that dissolved out of rocks, like inorganic sulfur compounds. The researchers proposed that pioneer microbes could quickly take advantage of newly opened ecological niches, like soils exposed during a glacier’s retreat, because of their efficiency at using scant resources.
They found that habitat generalists, on the other hand, tended to dominate older soils. This result suggested that the habitat specialists were eventually outcompeted by the slow and steady growth of the habitat generalists in a real-life turtle-and-hare race.
The team concluded that using multiple growth strategies helps microbes adapt to new environments. However, they acknowledged that ecological succession could occur differently in other landscapes, such as in the aftermath of volcanic eruptions, meteorite impacts, or forest fires. They suggested that future researchers work to uncover how microbial communities lay the groundwork across these diverse ecosystems.
The post When glaciers retreat, microbes take over appeared first on Sciworthy.
Scientists discovered a surprising gut-heart connection that may help prevent sleep apnea from causing serious cardiovascular damage. Sleep apnea affects millions of people worldwide and is known to raise the risk of serious cardiovascular problems. Now, researchers have identified a potential new treatment target that could help reduce some of the condition’s harmful effects. Findings [...]Single cells used past nutrient shocks to change how they grew.
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