What happens when macrophages refuse to eat the dead?

Macrophages, a type of immune cells, are an integral part of our body’s defense system. The term macrophage comes from two Greek words – makro meaning big and phagien meaning eat, which makes them the “big eaters”. And boy, do they love to eat! Some things that they like to chomp on include bacteria and other foreign substances, dying and dead cells, and cancer cells, thus, acting as the body’s cleanup system. This process of eating is not only important for defending against foreign pathogens but is also essential for cleaning up cell debris and maintaining normal bodily functions.

Macrophages typically encapsulate their food by surrounding it with cell extensions, then engulf it and digest it. Check out some cool videos of macrophages eating some bacteria here. This process of eating is typically called “phagocytosis”. However, the term for macrophages eating dying cells is called “efferocytosis”. This term is derived from the Latin word efferre which translates to “take to the grave” or “to bury”. When this mechanism of disposal of cellular corpses goes wrong, the rotting dead cells can lead to inflammation that damages the surrounding tissue. This can lead to many diseases, including coronary artery disease, chronic obstructive pulmonary disease, cystic fibrosis, and rheumatoid arthritis. In a recent publication from the Tabas lab, Dr. Kasikara and Columbia postdoc Dr. Schilperoort explore the molecular mechanisms that underlie impaired efferocytosis and how that leads to the formation of dangerous plaques in the arteries that supply blood to your heart. The buildup of these plaques leads to a condition called coronary artery disease which remains the leading cause of deaths in the United States, causing about 1 in 4 deaths.

Significant advances in genomic sequencing in the past few years have led to the discovery of several mutations that are often correlated with the occurrence of coronary artery disease in patients. One of these mutations is in a gene encoding a protein called PHACTR1. However, because the mutation is present in a part of the gene outside of where the protein-coding sequence lies, it was unclear if this mutation disrupted efferocytosis by disrupting the function of PHACTR1. PHACTR1 regulates the ability of various cell types to expand, contract, and move. While the ability of macrophages to execute these motions is required to engulf or eat cells, whether PHACTR1 is involved in this process in macrophages and thereby macrophage efferocytosis was not known. In this study, the authors made two important discoveries. Firstly, they found that PHACTR1 is essential for macrophage efferocytosis. Secondly, they found that the mutation decreases the expression levels of PHACTR1. The authors investigated more and established that PHACTR1 is important for maintaining an activated version of a motor protein called myosin which is required for cellular movement. Thus, lower levels of PHACTR1 hamper the ability of macrophages to eat dead cells by disrupting cellular movement. This contributes to the buildup of dying cells in our arteries and a consequent increase in the risk of heart attack and stroke.

Fig 1. Model depicting the relationship between efferocytosis and risk of coronary artery disease. Reduced levels of efferocytosis lead to insufficient clearance of dead cells and consequent plaque formation in the arteries. Figure adapted from Kasikara, JCI 2021.

The results from this study provide novel insights into the role of PHACTR1, myosin, and other associated proteins in the pathogenesis and progression of coronary artery disease. Before this study was performed, we only knew that there was a correlation between an increased risk of heart disease and a mutation in PHACTR1 gene. The authors performed rigorous experiments and demonstrated that the mutation changes PHACTR1 production and that this causes heart disease. This information is extremely valuable as it provides a basis for designing future therapies. For example, increasing PHACTR1 production artificially may be an effective strategy for treating coronary artery disease. As defective macrophage efferocytosis is also involved in the pathogenesis of many other diseases, this study has direct implications for the discovery of new treatment paradigms for these diseases as well.

Ancestry connects non-cancer causing mutations in cancer patients

The cause of cancer as a disease has been partly attributed to genetics across a diverse range of populations. However, it is unclear whether cancer patients carry additional genetic mutations, also known as variants, in non-cancer causing genes and if these variants are evolutionarily related. Because ancestry-specific variants were more recently generated in evolutionary time, they could have been easily missed in analyses where all patients were cumulatively analyzed without consideration for ancestry. A recent concept proposed by geneticists suggests that people are more likely to develop or be protected from diseases based on recently acquired mutations and are less so due to more distant mutations. This is an interesting theory that scientists can now test using genome information from more than 10,000 cancer patients whose ancestries are known. So far, how mutations affect gene expression – whether they completely abolish the expression of gene products (e.g. protein) or result in the creation of a misshapen protein, have only been reported for variants present in patients with European ancestry. The remaining ancestries are yet to be explored.


Advances in sequencing technology have made it easier for researchers to access genome sequencing information under clinical settings and for healthcare providers to share personalized diagnoses as part of ‘genomic medicine’ to patients. Using publicly available genome sequencing data for cancer patients, Dr. Xiao Fan and colleagues analyzed the variants in non-cancer causing genes and in “medically actionable” genes in 10,389 cancer patients. The authors found 1.46 billion mutations, which were then filtered through rigorous quality testing of sequencing information followed by expert geneticist review, resulting in a final total reliable set of 2,920 non-cancer related pathogenic and likely pathogenic variants. About 750 of these variants were harbored on average within a quarter of the cancer cases, no matter the heritage. A surprising majority (~27%) of the total variants were displayed in patients with European ancestry, followed sequentially by Latinx/Native American (15%), African American (13%) and East Asian (12%) patients.


Because genetic mutations can affect expression of proteins, the authors then dug deep into the variant data to examine whether these variants behaved in an expected manner on a molecular level. When genes contain mutations that cause the protein it encodes to be a shorter version of itself, the mutation is referred to cause a protein “truncation”. Sometimes, a truncating mutation in a gene can trigger a decrease in expression at the messenger RNA (mRNA) level even before the mRNA is used to make the protein. To find out if the variants that produced truncated gene products underwent changes at the mRNA level, the authors measured the gene expression levels of such variants. Of the variants that showed a meaningful difference in gene expression compared to non-cancer patients, a large majority of variants showed a decrease in expression. This result indicated to the authors that truncation-causing variants often work at the mRNA level even before the cells spend energy to make the disease-associated proteins. The authors then examined the behavior of gene variants that do not cause truncations but rather cause just a single swap in the gene sequence, known as “missense” variants. Missense mutations typically only cause a change in one or two building blocks of the protein but do not affect the abundance of the protein itself. Surprisingly, the authors found that the missense variants in their data are unusually regulated in the cancer patients at the mRNA level resulting in a decrease in gene, and therefore, protein expression. This is an uncommon observation, making the authors speculate that missense variants are perhaps controlled by gene-expression independent mechanisms within the cancer patients’ cells.

This study provides a testament to the power of genomic medicine that can be used to complement conventional medical treatment. With a strong sample of ~10,000 cancer patients, this report stands as one of the most comprehensive studies that considers race and ancestry in its analysis. While genomic profiling is becoming more common in medical diagnoses, this study further provides a reason for understanding diseases and invention of medicine based on race, ethnicity and genetic heritage.

Identifying a potential risk factor for alcohol abuse among victims of violence in childhood

Half of all children in the United States have been physically assaulted in their lifetime, according to a 2014 study. This finding is alarming, especially considering that childhood maltreatment and abuse can lead to numerous negative mental health outcomes. 

Researchers and medical professionals around the globe often focus on adverse childhood experiences and their detrimental effects on development. Experiencing threat and violence is frequently correlated with a decreased ability to effectively handle negative emotions and heightened emotional reactivity relative to those who have not experienced such trauma. For instance, a typical situation such as having your toy taken away by a peer in school might invoke an explosive, angry response from a child who has been a victim of abuse. Moreover, research demonstrates that children who have faced abuse are also more likely than others to interpret ambiguous actions (such as a classmate accidentally bumping into them in the hallway) as confrontational.

How might those who’ve experienced violence in their childhood, and also have trouble dealing with negative emotions, respond to everyday stressors (i.e. getting through hard homework sets or dealing with long waits for customer service on the phone)? Dr. Charlotte Heleniak and her colleagues studied this response, called distress tolerance, in a newly published paper.

Levels of distress tolerance vary among different individuals. Someone with low distress tolerance is extraordinarily uncomfortable in situations where they’re facing a challenging obstacle, upset, or experiencing negative emotions that can make it hard to persist in the face of difficulty. They have a harder time working through these difficult events compared to people with higher distress tolerance. Research also shows that people with low distress tolerance may find it necessary to escape bad feelings by seeking immediate relief. This relief can often take the form of substance abuse. 

Additionally, while little research has been done, distress tolerance may make an individual more vulnerable to other mental health problems such anxiety and depression. Because of this, Dr. Heleniak’s team examined whether low distress tolerance is associated with these two mental illnesses, as well as alcohol abuse.

teens drinking
Image from Pixabay

Propensity toward problematic alcohol use in adolescents involves many environmental risk factors such as sociodemographic factors and parental drinking behavior. These can be difficult or impossible to address therapeutically. However, if distress tolerance is indeed tied to substance abuse, this may offer a clearer path toward crafting a psychological intervention. 

Dr. Heleniak and her colleagues studied 287 16- to 17-year-old participants across a broad range of socioeconomic backgrounds. They asked the teens about previous violence exposure in their personal life, and assessed depression, anxiety, and alcohol use. Four months later, they reassessed these parameters.

To examine the teens’ distress tolerance, the researchers used a measure called the Paced Auditory Serial Addition Task, which measures a person’s persistence on a difficult task. The sooner a participant decides to terminate the task, the lower their distress tolerance. The team found that those teens who experienced a heighted amount of violence did indeed have lower distress tolerance. At the initial time point, lower levels of distress tolerance were not associated with any of the three psychopathologies (i.e. alcohol abuse, anxiety, depression).

However, the researchers found that low distress tolerance predicted alcohol abuse from the first time point to the second, about 4 months later. Low distress tolerance was not associated with anxiety or depression at either of the two time points of data collection.

Figure 1. Teens who experienced more abuse and violence had lower distress tolerance. Four months after the initial assessment, teens who had low distress tolerance were even more likely to have developed problematic drinking behaviors.

Based on their findings, Dr. Heleniak and her team conclude that researchers could potentially pinpoint distress tolerance as a way to target teens’ problematic use of alcohol, especially those who have experienced violence. Indeed, therapeutic programs aimed at improving distress tolerance already exist. The authors explain that treatments such as Dialectical Behavior Therapy (DBT) and mindfulness practices may be particularly useful. 

Given that teen alcohol abuse may continue into adulthood and lead to dependency issues later in life, the findings of this study could go a long way to helping those adolescents who struggle with both addiction issues and an abusive past.

If you or someone you know is experiencing substance dependency problems, SAMHSA (1-800-662-HELP) is a free, confidential, resource available 24/7 365-days a year.

Charlotte Heleniak is a postdoctoral scientist in the Developmental Affective Neuroscience Lab at Columbia University. She received her Ph.D. in Child Clinical Psychology from the University of Washington. She focuses on how childhood adversity impacts emotion regulation and social cognition in ways that predict adolescent psychopathology. This research has earned her awards from the National Institute of Mental Health and the Doris Duke Charitable Foundation, as well as the Sparks Early Career Grant from the American Psychological Foundation.

Shedding light on transfers in soccer – from a physicist’s point of view

Ever wondered about the connection between sports, architecture and molecular physics? These three distinctive fields come together when we talk about fullerenes. Fullerenes are a modification of carbon with some very interesting properties. The most outstanding one is their structure: They are hollow spheres made up of several penta- and hexagons, resembling a cage. The most famous fullerene C60 (Fig. 1a) actually looks very similar to the traditional pattern of a soccer ball (Fig. 1b). Fullerenes are named after the American architect Richard Buckminster Fuller who is famous for his constructions of geodesic domes, very similar to the fullerenes structure (Fig. 1c). Therefore fullerenes are commonly referred to as Buckminster Fullerenes or Bucky Balls. Fullerenes can build a unique molecular structure where atoms, molecules or even other small clusters are bound inside of the cage. These molecules are called endohedral molecules, with Ho3[email protected]80 (Fig. 1d) being an example introduced later in this text.

3D structure of fullerenes in comparison with a soccer ball and a geodesic dome
a) The carbon cage structure (grey) of C60 with the typical pentagons (orange) and hexagons (purple). b) The same structure can also be found in a classical design of a soccer ball. c) The Biosphère in Montreal, designed by R. B. Buckminster. d) The molecule used in the study, Ho3[email protected]80.

Endohedral molecules have gained some attention in biochemical research for two reasons. First, they are considered excellent vehicles to transport drug molecules to specific locations and release the cage’s content by an externally triggered mechanism. Second, they could be applied in radiotherapy, since the ability to carry metal atoms inside allows them to release a large amount of electrons which cause very localised cell damage, especially to cancer cells.

One mechanism which is expected to play an important role for these two applications is the so-called intermolecular coulombic decay (ICD, not to be confused with the International Classification of Diseases). In an atom, electrons are bound to the nucleus in so-called shells which layer above each other like an onion (a property they share with ogres). To remove an electron from its shell one has to supply energy to it, the closer to the nucleus the shell is, the more energy is needed. A common way of supplying this energy is to shine high-energetic light onto the atoms, either ultraviolet (UV) or even X-rays. If an electron is removed from an atom, we call the remaining atom an ion. If an inner electron is removed, a vacancy or “free spot” in that shell is created. Such ions are called excited.

Speaking from personal experience, excitement tends to decay quickly (citation needed), which also holds true for ions. Within an ion, an electron from a higher shell “falls down” (decays) into the vacancy of the inner shell. By doing so it has to give up the difference in energy between the two shells. One way to give up its energy is by emitting a photon, meaning shining light. This effect is used for example in neon bulbs. If the two involved shells are far enough from each other, the electron can transfer its energy to another electron which is then removed from its shell. This process is called the Auger effect (Fig. 2a). Within molecules another process can happen: The decaying electron can transfer its energy onto an electron of another atom in the molecule which then gets removed from its shell (Fig. 2b). This is the aforementioned ICD.

scheme of the auger effect and ICD in molecules and endohedral fullerenes
a) Schematic of the Auger effect. b) ICD in a normal molecule. c) ICD in an endohedral molecule.

Unfortunately, ICD in endohedral molecules (Fig. 2c) has, even though theoretically predicted, not been discovered. Well, until recently. Dr. Razib Obaid and colleagues set up an experiment at the Advanced Light Source (ALS) in Berkeley, one of the world’s brightest UV and X-ray light source facilities in the world. They used the UV light to radiate the molecule Ho3[email protected]80 (a molecule consisting of three holmium and one nitrogen atom, trapped in a cage of 80 carbon atoms). The result was the production of ions and electrons, which the researchers measured together with their energy distribution. Additionally, they measured the relation of the particle’s production time. Putting these measurements together, they were able for the first time to demonstrate ICD in endohedral molecules. This required not only a clever experimental setup, but also a lot of theoretical effort. The complexity of the experiment and its analysis derives from the fact that ICD involves multiple atoms with many electrons. This makes the measured spectra resulting from  such experiments difficult to disentangle and complicates the assignment of each individual process.

With the first clear observation of ICD in endohedral fullerenes, demonstrating the existence of the proposed mechanism, the researchers have opened the door to further research on the application of the process as a drug delivery system and its influence in the propagation of radiation induced molecular damage in biomolecules.

Dr. Razib Obaid is currently a postdoc at RARAF Radiological Research Accelerator Facility located at the Nevis Laboratory of Columbia University, lead by Dr. David J. Brenner.


Figure 1b: Derived from Football (soccer ball).svg. (2020, September 23). Wikimedia Commons. Retrieved 23:10, August 30, 2021

Figure 1c: Biosphere, Montreal.jpg. (2020, October 26). Wikimedia Commons,. Retrieved 23:11, August 30, 2021

Over the brainbow with a new PAL

Brains come in a variety of sizes. Several orders of magnitude separate the convoluted human brain from that of the fruit fly. But no matter the configuration, neuroscientists strive to study neurons in further and further detail, ideally at the single-cell level. However, consistently identifying individual neurons is not an easy endeavor; in most organisms there are so many neurons that even when labelled with colored tags we can’t see the forest for the trees.

Enter Caenorhabditis elegans, a worm with only 302 neurons. This tiny transparent worm comes in handy for scientists because they can easily follow the fate of any of its cells from the embryonic stage to adulthood. However, despite the somewhat predetermined developmental paths, the exact spatial location of each cell is slightly variable. Therefore, studies examining individual cell identities are doomed if they rely exclusively on relative position within each group of neurons.

In their recent paper, Dr. Eviatar Yemini and colleagues introduce a solution to this problem in the form of deterministic fluorescent labelling of all 302 neurons of the worm C. elegans. Their approach, NeuroPAL (a neuronal polychromatic atlas of landmarks), produces the same pattern of colors across worms, which makes a fundamental improvement to previous similar techniques like Brainbow that produce random patterns.

The first challenge they faced was determining how many distinguishable colors they needed to correctly identify all neurons. Fortunately, the neurons of this worm are dispersed over its whole body, grouped in 11 different clusters, so they didn’t need all 302 to be labelled with distinct colors. The biggest of these ganglia contains roughly 30 neurons, so aiming for a range of colors around that number was enough. How do you get those colors? One could achieve a sizable palette by using just a few different fluorescent markers or “fluorophores” that are detectable at different intensities. However, selecting the final fluorophores wouldn’t have happened without a great example of scientific collaboration. Dr. Yemini had been struggling with the colors blending together until he contacted a colleague who told him about a new fluorophore, and this ended up being the missing puzzle piece he needed to achieve all the distinguishable fluorophores. Once they had carefully selected the three distinct markers, a clever trick of imaging them in red, blue and green, allowed them to obtain a whole RGB palette of colors.

The next step was to achieve the different levels of each fluorophore for each neuron in a consistent way across worms by changing the signal driving the fluorophores’ expression. Starting from a list of 133 previously published genes with different patterns of neuronal expression, Dr. Yemini tried them all, painstakingly narrowing down the list to 41 winners by a process of iterative trial and error, checking the resulting color combinations and whether the neurons could be distinguished at each step. This process alone spanned more than two years, and required deep dives into the literature and some expert judgement calls: “in one rather desperate case, I guessed the expression from the behavioral phenotype and, very luckily, was approximately right” Dr. Yemini says.

Once they achieved the final combination of colors, they had finally created a genetically modified worm that could pass on this colorful and robust pattern for many generations.

A fluorescent image of a NeuroPAL worm with distinct labelling of each neuron
A NeuroPAL worm with deterministic fluorescent labelling of its 302 neurons. Notice that the head, on the left, has a much higher density of neurons, which had previously complicated the task of identifying them. Courtesy of Dr. Yemini.

NeuroPAL is not only a technical feat in and of itself, but was also a creative outlet for Dr. Yemini, who enjoyed the highly collaborative art-meets-science project:

“In high school, I had to choose between applying to art school or following what I thought was a more traditional route. I loved the artistic process, I’d taken many art classes and even managed to score a scholarship for an after-school art program at SUNY Purchase. But I let luck guide my fate and ended up taking the non-artistic route. I really miss that part of me. The process of making NeuroPAL has felt like a taste of a part of me that I’d lost.”

So what do you do after you create a tool that allows you to unambiguously identify all neurons? You use it to explore more questions! Dr. Yemini and his colleagues applied their shiny new worms to study many old questions in the field. For example, they leveraged the individual cell identification to refine whole-brain activity imaging, with which scientists previously had the issue of being unable to determine neuronal identity. They succeeded in recording responses to different chemical stimuli, both attractive and repulsive, confirming previous results and adding new neurons to the response pathways, thus unraveling more complex neuronal networks. On the whole, they show that this new tool can be used for exploring a variety of questions in C. elegans.

Sped-up video of a NeuroPAL worm responding to a stimulus. The cells that are activated by the stimulus shine more brightly and are identifiable by their underlying color.

You might be thinking, “This is all very cool, but what does a tiny transparent worm have to do with me?” While studying C. elegans in itself can shine light on some basic biological processes, it can also open the door to discoveries in more complex organisms and those more similar in neural organization to humans. Indeed, the authors suggest that this approach to unequivocally label cells could be translated to other models that are widely used in biomedical research, such as the fruit fly, fish and even mice. We still have a long way to go before we can create an entire rodent with a consistent pattern of shiny cells, but local labelling may be a more attainable goal. And eventually, this research will help us distinguish the trees from the forest.

Dr. Eviatar Yemini  is an Adjunct Associate Research Scientist in the Department of Biological Sciences at Columbia University (Hobert lab). He will be starting his own lab at the University of Massachusetts Medical School in January 2022. Reach out to him for exciting job opportunities!

Beneath The Surface Of Healing Wounds

With an average weight of ~12 kg and surface area of ~2m², skin is the largest organ of the body and is made up of three layers: epidermis, dermis, and hypodermis. Epidermis, the outermost layer, is composed of densely packed epithelial cells. Under the epidermis lies the dermis, which mainly contains blood vessels, hair follicles and sweat glands. The third layer, the hypodermis, is composed of loose connective and fatty tissue (Fig. 1). Given its large area and exposure to external elements, the skin is susceptible to injury, ranging from minor bruises to cuts, lacerations, and tears. The skin’s response to insults like these is a process well-known as wound healing, which occurs in three stages: inflammation, proliferation, and tissue remodeling. These stages work together in an overlapping sequential manner to ensure complete wound healing. A failure in any of the normal wound healing stages leads to chronic wounding and aberrant scar formation as seen in burn injuries and scar tissue formations. A delay in wound healing can result in increased infections and permanent tissue damage as seen in patients with diabetes.

Fig.1. Schematic representation of the layers of skin.

During inflammation, there is an influx of immune cells to clear invading microbes and cell debris at the site of injury. This is followed by  the proliferation phase during which there is an increase in the production of epithelial cells  that will migrate to the outer edge of the site of injury to repair the wound and restore it back to its uninjured state.  An essential step in wound healing is the mobilization of stem cells for the formation of new epithelial cells. Skin stem cells are found in the basal layer of the epidermis and in the bulge area of hair follicles. Epidermal stem cells are actively involved in replenishing cells as skin undergoes normal homeostasis as well as during wound repair. Stem cells in the hair follicles, on the other hand have periodic patterns of rest and activity during hair growth. Following injury, however, hair follicular stem cells are also involved in rebuilding the epidermis to seal the open wound.

Interactions between the immune cells during the inflammation stage and stem cells during the proliferation stage of wound healing are important for efficient tissue repair to take place. Cytokines are signaling molecules produced by cells that are required for cell-cell communication to stimulate cell migration towards the site of injury. Molecular and cellular mechanisms to address the role of cytokines in mediating interactions between immune cells and stem cells during wound healing remain unexplained.

In a previous study, Pedro Lee and colleagues observed that mice that lacked the interleukin -1 receptor (IL-1R) for IL-1 cytokine had a delayed wound healing response. In the skin, IL-1 is released by damaged keratinocytes (keratin producing cells present in nails, hair and skin). and dysregulation of IL-1 has been associated with a number of skin diseases. Pedro Lee, Rupali Gund and colleagues conducted the current study to understand the mechanism behind delayed wound healing in IL-1R mutant mice. They analyzed the molecular and cellular interactions during wound healing using a genetically engineered mouse model in which the entire skin mimics the biological response of wound healing. This mouse model, which lacks the caspase 8 gene in the epidermis, exhibits a wound healing response even in the absence of injury, thereby providing the researchers with a large number of stem cells participating in a wound healing process. The authors studied the structure of tissues and gene expression patterns in the skin of these mice. The researcher additionally performed assays to analyze proliferation of cells by growing cells in the lab from the genetically engineered model and the mice lacking IL-1R. The researchers found that IL-1 mediates wound healing through activation of stem cell proliferation in two possible ways. The first is by activating dermal fibroblasts that will activate the epidermal stem cell to cover up the open wound (Fig.2.A). The second is the activation of a population of immune cells called gamma delta T(γδT)-cells. These cells in turn activate the resting stem cells found in the hair follicles. These activated stem cells then migrate from the hair follicle towards the site of the injury for wound healing. The researchers also found that IL-1 interacts with another cytokine, IL-7, and together they work to increase the number of active gamma delta T cells in wounded skin and secrete growth factors (Fig.2.B) thereby increasing the population of stem cells promoting wound healing.

Fig.2. Schematic of cytokine mediated interactions between cell types during wound healing. A. IL-1 mediated interactions between dermal fibroblasts and epidermal stem cells. B. IL-1 mediated interaction between immune cells (γδT) and stem cells. Image adapted from Lee, Gund et al., 2017

Normal wound healing is an important and complex physiological process to ensure timely healing to maintain skin integrity. It requires coordinated interactions between various factors, cells and cytokines at each healing stage. Lee, Gund and colleagues have identified a novel role for immune cells (γδT-cells) in tissue repair in addition to their well-established role of fighting infections. The ability of γδT cells to respond to IL-1 and, in turn, secrete growth factors that promote stem cell reparative activity expands the kind of functions that immune cells can perform in tissues in addition to their common role in immunity. Stem cell therapy and regenerative medicine shows great potential in the field of wound healing and skin regeneration.

This study reveals how immune cells communicate with stem cells during tissue repair and identifies new cellular interactions that can be targeted to prevent diseases in which wound healing is impaired. Such therapies will preclude need for invasive surgical interventions and skin graft procedures as a treatment for chronic wounds.

Dr. Rupali Gund is a postdoctoral research scientist in the department of dermatology at Columbia University Irving Medical Centre. Her research focuses on studying mechanisms in skin autoimmune diseases and finding new ways to design therapies to improve patient’s quality of life. 

Having the Guts to Live Forever

For most people, the famous words “Who wants to live forever?” by the British rock band Queen seem merely hypothetical. However, scientists have been trying to identify the secret of immortality for decades. Their research has revealed an important role of the biological clock in regulating lifespan. The biological clock is a natural timing device composed of small molecular “clocks” in cells throughout the body that together dictate circadian rhythm, a term that originates from the Latin words circa (around) and dies (day). As the name implies, circadian rhythm refers to all natural processes that have a period of roughly a day, such as the sleep/wake cycle, body temperature change, and release of hormones like melatonin and cortisol. Because organisms, including humans, lose circadian rhythmicity with age, scientists thought that loss of circadian regulation contributes to aging and limits lifespan. However, recent findings by Dr. Matt Ulgherait and colleagues from the Department of Genetics and Development at Columbia University, show that the relationship between circadian rhythm and lifespan is more complex than initially thought. 

Dr. Ulgherait studied the role of genes that regulate cell-intrinsic rhythms, so called “clock genes” in aging. To this end, he used the model organism Drosophila, also known as the fruit fly. Although the evolutionary distance between fruit flies and humans is large, they show a remarkably high degree of genetic similarity: about 75% of the disease-causing genes in humans match up with the genome of Drosophila. In addition, the relatively short lifespan of fruit flies of about 50 days makes them a very practical model for aging research. Dr. Ulgherait introduced loss-of-function mutations in four different clock genes in the flies, named “cycle”, “period”, “timeless”, and “clock”, and found that only disruption of cycle and clock decreased lifespan, while disruption of timeless and period surprisingly extended lifespan by about 15-20%. 

The researchers continued by investigating the specific role of period, named for its contribution to the length of circadian cycles, to find out how this gene negatively affects lifespan. Dr. Ulgherait observed that period mutant flies not only lived longer than their genetically intact counterparts, but were also leaner despite an increased food intake. Remarkably, nutrients that were taken up by the flies were not converted into storable energy but rather used for heat production, as reflected by a higher ability of period mutant flies to recover after a cold shock of 4 °C for 1 hour. When burning of nutrients is disconnected from energy production, the metabolic machinery in the cell is considered to be “uncoupled”, a process regulated by so-called “uncoupling proteins”. Dr. Ulgherait found that the expression of uncoupling proteins was consistently high in period mutant flies. Moreover, disruption of uncoupling proteins reverted lifespan of period mutants to that of control flies, indicating that uncoupled energy metabolism and increased heat generation is important for longevity.

To determine which organ of the body is responsible for the effect of period on aging, the researchers removed the gene from different tissues one by one. This way, they found that loss of the period gene in the intestine was sufficient to increase lifespan. Intestinal expression of uncoupling proteins was required for the increased lifespan in period mutant flies, indicating that an uncoupled energy metabolism in the gut is essential for longevity. To understand the underlying mechanism through which uncoupled energy metabolism in the intestine regulates lifespan, Dr. Ulgherait examined intestinal functions that are affected by aging, including intestinal barrier function, which deteriorates with aging and makes the intestines more leaky. The scientists assessed intestinal barrier function in period mutant flies by performing the “smurf assay”. This assay, named after the children’s cartoon, measures leakage of an ingested blue dye which makes the fly resemble a smurf (see image below). Indeed, period mutant flies showed a lower percentage of “smurfs” relative to controls, indicating less intestinal leakiness. Thus, loss of the circadian period gene protects against aging-related intestinal dysfunction. 

Photograph showing a normal-colored fruit fly (bottom left) with an intact intestinal barrier function and “smurf” flies (right and top left) with a disrupted intestinal barrier function. Source: The Scientist.

In summary, the research by Dr. Ulgherait and colleagues shows that disruption of circadian rhythm affects lifespan by modulating uncoupled energy metabolism in the gut. Although this research was performed in Drosophila, genetic variability in uncoupling proteins has been shown to predict longevity in humans. Therefore, pharmacological targeting of uncoupling may be one of the keys for increasing lifespan. So perhaps we should avoid hypotheticals and actually start asking the question: “Would you want to live forever?”


Mind the (small) gap between the mammal and non-mammal navigation system

Remembering where we left our keys, the distance between the platform and the train, or where the TV remote control was placed last night, are examples of daily events that require spatial memory, i.e., the ability to recall spatial locations. This ability is made possible by neurons called place cells, which are mainly located within a brain region known as the hippocampus. While we navigate spaces, place cells encode information from environmental cues, creating a sense of space. Place cells were discovered by Dr. John O’Keefe, who, together with Drs. May-Britt Moser and Edvard I. Moser, was awarded with the Nobel Prize in Medicine and Physiology in 2014. The so-called ‘inner GPS’ of the brain is shared across species and has been identified in mammals including rodents, primates, and bats, which are particularly known for their spatial abilities.

In a recent article in Science, Columbia postdoc Dr. Payne and colleagues investigated whether this navigation system also exists in non-mammals with pronounced spatial memory skills. The authors chose to study tufted titmice, birds that accumulate seeds in multiple locations to prevent a shortage in case of decreased food supply. In the lab, the authors recorded hippocampal activity of tufted titmice while they were navigating in an arena for sunflower fragments. They identified neuronal activity similar to rodent place cells. Also, they observed a mammalian-like distribution of those cells along the hippocampus. These observations suggest that the mechanisms of hippocampal coding in birds exhibit similarities to those identified in mammals.

The authors compared results from the titmouse with the activity and hippocampal organization of zebra finch, a non-food-caching bird. They found that the subregion of the hippocampus with the highest density of place cells was larger and more populated in tufted titmice than in zebra finches. These findings suggest that place cells are more spatially informative and stable in tufted titmice compared to the place cells in zebra finches. Such differences in spatial coding between bird species might be due to differences in demands of food caching.

In this work, Dr. Payne and colleagues identified for the first time neuronal activity in a non-mammalian hippocampus similar to mammalian-like place cells. Furthermore, they reveal evidence that spatial encoding may differ between species mainly due to its functional demand. Despite a divergent evolution from millions of years, mammals and non-mammals possess a similar version of their GPS cells.

 Dr. Hannah Payne is a postdoctoral fellow at Dr. Dmitriy Aronov‘s lab in the Zuckerman Mind Brain Behavior Institute at Columbia University.

CRISPR versus acute lymphoblastic leukemia

Acute lymphoblastic leukemia (ALL) is an aggressive form of cancer arising from malignant transformation of immature cells that were otherwise fated to become white blood cells, or lymphocytes. ALL occasionally affects adults but is more commonly a pediatric cancer: children under the age of 5 have the highest risk of being affected. Upon diagnosis, it is possible to treat ALL with an aggressive regimen of multiple chemotherapy drugs that is successful for over 80% of patients. Unfortunately, when tumors reappear after initial treatment, in relapse, the cases become extremely difficult to treat. Additionally, the cellular landscape of ALL in relapse has a high degree of genetic heterogeneity and variability between different patients. Oncologists and cancer biologists suspect it is this genetic complexity that makes ALL in relapse especially hard to fight in the clinic. 

In a study published in Nature Cancer last year, Dr. Jessie Brown and colleagues set out to improve outcomes for patients with ALL by clarifying how mutational complexity in relapsed tumors interacts with chemotherapy drugs to resist treatment. To this end, the team first employed extensive genetic sequencing on ALL samples collected upon diagnosis, remission, and relapse in order to identify the mutational landscape that distinguishes relapse tumors from the others. Samples were collected from 175 patients in total – 149 from pediatric cases and 26 from adults. Next, in order to functionally characterize the mutations they identified, the authors used a genome-wide genetic screening strategy to identify drug–gene interactions and determine why the relapse-specific mutational landscape is less responsive to chemotherapy. The screen was carried out in a representative model ALL cell line using CRISPR, a genetic editing tool used to specifically activate or inhibit the expression of single genes. 

Fig 1. Schematic of experimental design for CRISPR-based screen in ALL model cell line. A library of targeting molecules called guide RNAs (gRNAs) was used to activate or inhibit genes identified to have mutations associated with ALL in relapse. Figure adapted from Oshima, Zhao, Durán, Brown, et al. 2020.

Between these two approaches, the team succeeded in characterizing relapse-specific mutations that arise during the administration of chemotherapy itself, a process known as clonal evolution. Additionally, the number of mutations they identified increased with patient age at diagnosis, a finding that allowed the researchers to establish that the most recent commonality between the mutant cells present at diagnosis versus later at relapse often develops early, years before the leukemia is officially diagnosed. Importantly, this finding is consistent with the hypothesized fetal origin of many pediatric ALLs, which postulates that chromosomal abnormalities leading to cancer are already present at birth. It is also consistent with the higher rate of relapse previously observed in adult patients.

When the mutations uniquely acquired during relapse were further investigated using CRISPR screening in an ALL model cell line, a strong positive selection was revealed for those that conferred chemotherapy resistance. By using CRISPR to manipulate the expression of genes affected by each mutation of interest and assessing how the ALL model cells fared in each experiment, the researchers were able to analyze the relationships between the effect of the mutation and application of each drug. Of the drugs investigated, functional overlaps in the cellular mechanisms mediating the activity of each were identified between several groups of them. The significance of this finding is two-fold. First, it helps researchers and medical providers understand why the presently used multi-drug regimen might be effective for ALL in the first place. Second, it suggests that other drugs acting via similar mechanisms of action could be effective treatments in the future. Moving forward, ALL in relapse might be treated not just with combinatorial chemotherapy, but with specific combinations, doses, and schedules of drugs that meet the personalized genetic vulnerabilities of specific ALL cases. 

One inhibitor tested in the study’s cell-based CRISPR screen, an inhibitor called ABT-199, also known as Venetoclax, is already being tested for inclusion as a new therapeutic. If approved, it could become part of the arsenal of drugs used to compose personalized chemotherapeutic cocktails for patients with ALL in relapse. According to co-first author Dr. Brown, “it is currently in Phase I/II clinical trials for relapsed ALL and other malignancies and we hope that this work and our follow-up studies can further underscore the mechanisms of action of this inhibitor in combination with commonly used chemotherapies.” 

Altogether, this study identified a number of mutations that make relapsed ALL distinct from ALL before treatment with chemotherapy and functionally characterized the interactions of these mutations with multiple chemotherapy drugs. While ALL is not a common cancer – it accounts for less than 0.05% of all incidences of cancer in the United States – those affected must be treated with aggressive chemotherapy that can negatively affect the lives and health of patients in many ways. Because of this, understanding how to better target ALL at diagnosis and treatment-resistant ALL in relapse is a high priority for researchers. The findings of this work help to identify targets for reversing chemotherapy resistance and improving treatment outcomes for pediatric and adult patients alike. 

Dr. Jessie Brown is a postdoctoral research fellow in the Ferrando Lab at Columbia University Irving Medical Center studying therapeutic resistance in relapsed acute lymphoblastic leukemia.  

Random Walking – When having no clue where to go still makes you reach your destination

In empirical sciences, theories can be sorted into three categories with ascending gain of knowledge: empirical, semi-empirical and ab initio. Their difference can best be explained by an example: In astronomy the movement of all planets was known since ancient times. By pure observation astronomers could predict where in the sky a certain planet would be at a given time. They had the knowledge of how they moved but actually no clue why they did so. Their knowledge was purely empirical, meaning purely based on observation. Kepler became the first to develop a model by postulating that the sun is the center of the planetary system and the planet’s movement is controlled by her. Since Kepler could not explain why the planets would be moved by the sun, he had to introduce free parameters which he varied until the prediction of the model matched the observations. This is a so-called semi-empirical model. But it was not until Newton who with his theory of gravity could predict the planets movements without any free parameters or assumptions but purely by an ab initio, latin for “from the beginning”, theory based on fundamental principles of nature, namely gravity. As scientists are quite curious creatures, they always want to know not only how things work but also why they work this way. Therefore, developing ab initio theories is the holy grail in every discipline.

Luckily, in quantum mechanics the process of finding ab initio theories has been strongly formalized. This means that if we want to know the property of a system, for example its velocity, we just have to kindly ask the system for it. This is done by applying a tool, the so-called operator, belonging to the property of interest on the function describing the system’s current state. The result of this operation is the property we are interested in. Think of a pot of water. We want to know its temperature? We use a tool to measure temperature, a thermometer. We want to know its weight? We use the tool to measure its weight, a scale. An operator is a mathematical tool which transforms mathematical functions and provides us with the functions property connected to the operator. Think of the integral sign which is an operator too. The integral is just the operator of the area under a function and the x-axis.

The problem is, how do we know the above mentioned function describing the system’s state? Fortunately, smart people developed a generic way to answer this problem too: We have to solve the so-called Schrödinger equation. Writing down this equation is comparably easy, we just need to know the potentials of all forces acting on the system and we can solve it. Well, if we can solve it. It can be shown that analytical solutions, that means solutions which can be expressed by a closed mathematical expression, only exist for very simple systems, if at all. For everything else numerical approaches have to be applied. While they still converge towards the exact solution, this takes a lot of computational time. The higher the complexity of the system, the more time it takes. So for complex systems even the exact numerical approach quickly becomes impractical to use. One way out of this misery is simplification. With clever assumptions about the system, based on its observation one can drastically reduce the complexity of the calculations. With this approach, we are able to, within reasonable time, find solutions for the problem which are not exact, but exact within a certain error range.

Another way to find a solution for these complex problems is getting help from one of nature’s most powerful and mysterious principles: chance. The problem of the numerical exact solving approach is that it has to walk through an immensely huge multidimensional space, spanned by the combinations of all possible interactions between all involved particles. Think billions of trillions times billions of trillions. By using a technique called Random Walking the time to explore this space can be significantly reduced. Again, let’s take an example: Imagine we want to know how many trees grow in a forest. The exact solution would be dividing the forest into a grid of e.g., 1 square foot, and counting how many trees are in each square. A random walk would start in the forest center. Then we randomly choose a direction and a distance to walk before counting the trees in the resulting square. If we repeat this just long enough we eventually will have visited every square, therefore knowing the exact number, meaning the random walk converges towards the exact result. By having many people starting together and doing individual random walks stopping when their results deviation is below a certain threshold a quite accurate approximation can be obtained in little time.

Columbia postdoc Benjamin Rudshteyn and his colleagues developed a very efficient algorithm based on this method specifically tailored for calculating molecules containing transition metals such as copper, niobium or gold. While being ubiquitous in biology and chemistry, and playing a central role in important fields such as the development of new drugs or high-temperature superconductors, these molecules are difficult to treat both experimentally and theoretically due to their complex electronic structures. They tested their method by calculating for a collection of 34 tetrahedral, square planar, and octahedral 3D metal-containing complexes the energy needed to dissociate a part of the molecule from the rest. For this, precise knowledge of the energy states of both the initial molecule and the products is needed. By comparing their results with precise experimental data and results of conventional theoretical methods they could show that their method results in at least two times increased accuracy as well as increased robustness, meaning little variation in the statistical uncertainty between the different complexes.

molecule complex geometries
Figure 1: Illustration of the three types of geometry of the datasets molecules: Octahedral (a), square planar (b) and tetrahedral (c), with the transition metal being the central sphere. In (d) the dissociation of part of the molecule is shown.

While still requiring the computational power of modern supercomputers, their findings push the boundaries of the size of transition metal containing molecules for which reliable theoretical data can be produced. These results can then be used as an input to train methods using approximations to further reduce the computational time needed for the calculations.

Dr. Benjamin Rudshteyn is currently a postdoc in the Friesner Group of Theoretical Chemistry, lead by Prof. Dr. Richard A. Friesner, in the Department of Biological Sciences at Columbia University.

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