Around 500,000 people in the UK live with Inflammatory Bowel Disease (IBD), a life-long, chronic condition characterized by sporadic bouts of gut inflammation-causing debilitating symptoms. Crohn’s Disease and Ulcerative Colitis – the latter affecting around 1 in 400 people - are the two most common types of IBD. Current treatments are ineffective and seriously impact the quality of life of the patients and those of their families. 

Scientists at the Earlham Institute, Quadram Institute, and the University of East Anglia on the Norwich Research Park, have developed a new computational biology method to better understand IBD for targeted clinical treatments. By analyzing specific differences in gut cell types, the study deciphers cellular crosstalk to identify how beneficial bacteria communicate with our immune system to treat IBD and reduce gut inflammation.

The human gut harbors a community of microbes, known collectively as the microbiome, which is crucial to maintaining good health. A disrupted microbiome can cause gut-related conditions including IBD, an immune-linked inflammatory disease that causes abdominal pain, diarrhea, and extreme fatigue. 

People with IBD tend to have reduced diversity or a change in the balance in their gut microbiome, especially of Bacteroides and Firmicutes bacteria. However, we still don’t know how exactly this translates to the triggering and progression of IBD. By understanding how these bacteria interact with the gut lining and the immune system, and how this differs in IBD, we can better understand the causes and start developing targeted, effective treatments.

But to decipher this crosstalk across the different kingdoms of life, you need to understand how bacteria communicate, and then how human cells react to that information. This quest united microbiologist and immunologist Professor Simon Carding from the Quadram Institute and UEA, with Dr. Tamás Korcsmáros, a systems biologist whose expertise lies in cellular signaling networks from the Earlham and the Quadram Institutes. 

Professor Carding and his team have been investigating Bacterial Extracellular Vesicles (BEVs), which are tiny packages created by bacteria that they fill with various molecules and release from the cell. They can cross the gut lining, reaching cells of the immune system where they are recognized by receptors. The contents of the BEVs are molecular signals that then trigger the immune cells to react, with that signal potentially cascading into widespread effects.

In a healthy gut, BEVs and their cargo can contribute to anti-inflammatory responses of the immune system, but in an inflamed IBD patient’s gut, this response is lost. BEVs could therefore be used as a potential new therapy. But currently, we don’t understand enough about how they interact with the complex immune system. Our immune response relies on different types of cells monitoring for a plethora of different signals and interacting with each other to respond appropriately to a perceived threat of infection locally, and systematically across the body.

To address this knowledge gap, Dr. Tamás Korcsmáros and his team used a previously published dataset about which genes are actively making proteins in 51 types of colon cells, from either healthy conditions or under the effect of ulcerative colitis. Uniquely, this dataset contained inflamed and uninflamed data from the same patients, allowing investigation of the effect of inflammation and not only the complex disease.

The team also analyzed and characterized all of the cargo proteins obtained from BEVs made by the common gut bacterium Bacteroides thetaiotaomicron (Bt).

They then combined these datasets using an experimentally verified computational pipeline (called MicrobioLink) that predicts the interactions between microbial and host proteins, and how these trigger complex networks of cascading signaling systems. From this, they could build up an overall picture of which microbial proteins were able to interact with which human proteins in the different types of immune cells and identify the differences between these networks in a healthy gut and IBD.

This model, called an interactome, provides a snapshot of the constant communication between gut bacteria and our immune system. From this, the researchers could get an idea of the biological processes affected by microbial proteins - in healthy and inflamed UC conditions.

Their findings were published recently in the prestigious Journal of Extracellular Vesicles, one of the leading journals covering vesicle-mediated biological communication. The study was funded by the Biotechnology and Biological Sciences Research Council, part of UK Research and Innovation (UKRI).

Many interactions were identified as common across cell types, but the research uncovered many biological processes that were specific to one type of immune cell. Focussing specifically on one pathway known to be important in immunity and inflammation, they were also able to identify differences between the same cell types in healthy and ulcerative colitis conditions. Experiments using cell cultures grown together with BEVs validated the predictions from the computational modeling.

“The finding that BEVs affect the immune system’s pathways in a cell-type-specific manner, and that they are altered in inflammatory bowel disease is an important step to understanding the condition, and potentially could help in developing BEVs as a therapeutic system,” said Lejla Gul, first author on the paper and an iCASE Ph.D. student at the Earlham Institute and the Quadram Institute, supported by the BBSRC Norwich Research Park Biosciences Doctoral Training Partnership.

“Studying interkingdom connections with BEVs in a cell-type-specific resolution requires multi-disciplinary expertise and various ‘omics datasets. Then you need a computational pipeline to analyze the data from different patients. Besides the actual scientific results, in the paper we introduce an open-source pipeline that others can use to analyze their data" said Dr. Tamás Korcsmáros. “We hope that what we have demonstrated here in this study will be applied by others for understanding the mechanisms how other bacterial species communicate with our cells, and how it may be altered in other diseases.”

“This study highlights the importance and impact of laboratory scientists working with bioinformaticians to develop the means and tools for understanding the highly complex nature of the interactions between our gut microbes and cells of our body that is central to maintaining our health,” said Professor Simon Carding. “The insights gained from studies such as this will be invaluable in developing new interventions aimed at maintaining health by promoting beneficial interactions with gut microbes and preventing harmful ones that can lead to diseases such as IBD.”

"Extracellular vesicles produced by the human commensal gut bacterium Bacteroides thetaiotaomicron affect host immune pathways in a cell-type-specific manner that are altered in inflammatory bowel disease" is published in the Journal of Extracellular Vesicles. 

Researchers at the Institute for Chemical Reaction Design and Discovery and Hokkaido University, a Japanese national university in Sapporo, Hokkaido, have developed a virtual ligand-assisted (VLA) screening method, which could drastically reduce the amount of trial and error required in the lab during transition metal catalyst development. The method, published in the journal ACS Catalysis, may also lead to the discovery of unconventional catalyst designs outside the scope of chemists’ intuition.

Ligands are molecules that are bonded to the central metal atom of a catalyst, and they affect the activity and selectivity of a catalyst. Finding the optimal ligand to catalyze a specific target reaction can be like finding a needle in a haystack. The VLA screening method provides a way to efficiently search that haystack, surveying a broad range of values for different properties to identify the features of ligands that should be most promising. This narrows down the search area for chemists in the lab and has the potential to greatly accelerate the reaction design process.

This new work utilizes virtual ligands, which mimic the presence of real ligands; however, instead of being described by many individual constituent atoms—such as carbon or nitrogen—virtual ligands are described using only two metrics: their steric, or space-filling, properties and their electronic properties. Researchers developed approximations that describe each of these effects with a single parameter. Using this simplified description of a ligand enabled researchers to evaluate ligands in a computationally efficient way over a large range of values for these two effects. The result is a “contour map” that shows what combination of steric and electronic effects a ligand should have in order to best catalyze a specific reaction. Chemists can then focus on only testing real ligands that fit these criteria.

Researchers used monodentate phosphorus (III) virtual ligands as a test group and verified their models for the electronic and steric properties of the virtual ligands against values calculated for corresponding real ligands.

The VLA screening method was then employed to design ligands for a test reaction in which a CHO group and a hydrogen atom can be added to a double bond in two different possible configurations. The reaction pathway was evaluated for 20 virtual ligand cases (consisting of different assigned values for the electronic and steric parameters) to create a contour map that shows a visual trend for what types of ligands can be expected to result in a highly selective reaction.

Computer models of real ligands were designed based on parameters extracted from the contour map and then evaluated computationally. The selectivity values predicted via the VLA screening method matched well with the values computed for the models of real ligands, showing the viability of the VLA screening method to provide guidance that aids in rational ligand design.

Beyond saving valuable time and resources, corresponding author Satoshi Maeda anticipates the creation of powerful reaction prediction systems by combining the VLA screening method with other computational techniques.

“Ligand screening is a pivotal process in the development of transition metal catalysis. As the VLA screening can be conducted in silico, it would save a lot of time and resources in the lab. We believe that this method not only streamlines finding an optimal ligand from a given library of ligands, but also stimulates researchers to explore the untapped chemical space of ligands,” commented corresponding author Satoshi Maeda. “Furthermore, we also expect that by combining this method with our reaction prediction technology using the Artificial Force Induced Reaction method, a new computer-driven discovery scheme of transition metal catalysis can be realized.”

Read more https://www.supercomputingonline.com/categories-media/how-to-style/shape-shifting-robots-video

Physicists have discovered a new way to coat soft robots in materials that allow them to move and function in a more purposeful way. The research, led by the UK's University of Bath, is described today in Science Advances. 

The authors of the study believe their breakthrough modeling on ‘active matter’ could mark a turning point in the design of robots. With further development of the concept, it may be possible to determine the shape, movement, and behavior of a soft solid not by its natural elasticity but by human-controlled activity on its surface.

The surface of an ordinary soft material always shrinks into a sphere. Think of the way water beads into droplets: the beading occurs because the surface of liquids and other soft material naturally contracts into the smallest surface area possible – i.e. a sphere. But active matter can be designed to work against this tendency. An example of this in action would be a rubber ball that’s wrapped in a layer of nano-robots, where the robots are programmed to work in unison to distort the ball into a new, pre-determined shape (say, a star).

It is hoped that active matter will lead to a new generation of machines whose function will come from the bottom up. So, instead of being governed by a central controller (the way today’s robotic arms are controlled in factories), these new machines would be made from many individual active units that cooperate to determine the machine’s movement and function. This is akin to the workings of our own biological tissues, such as the fibers in heart muscle.

Using this idea, scientists could design soft machines with arms made of flexible materials powered by robots embedded in their surfaces. They could also tailor the size and shape of drug delivery capsules, by coating the surface of nanoparticles in a responsive, active material. This in turn could have a dramatic effect on how a drug interacts with cells in the body.

Work on active matter challenges the assumption that the energetic cost of the surface of a liquid or soft solid must always be positive because a certain amount of energy is always necessary to create a surface.

Dr. Jack Binysh, study first author, said: “Active matter makes us look at the familiar rules of nature – rules like the fact that surface tension has to be positive – in a new light. Seeing what happens if we break these rules, and how we can harness the results, is an exciting place to be doing research.”

Corresponding author Dr. Anton Souslov added: “This study is an important proof of concept and has many useful implications. For instance, future technology could produce soft robots that are far squishier and better at picking up and manipulating delicate materials.”

For the study, the researchers developed theory and simulations that described a 3D soft solid whose surface experiences active stresses. They found that these active stresses expand the surface of the material, pulling the solid underneath along with it, and causing a global shape change. The researchers found that the precise shape adopted by the solid could then be tailored by altering the elastic properties of the material.

In the next phase of this work – which has already begun – the researchers will apply this general principle to design specific robots, such as soft arms or self-swimming materials. They will also look at collective behavior – for example, what happens when you have many active solids, all packed together.