macrophage
How to Feed a Macrophage
Posted on by Lawrence Tabak, D.D.S., Ph.D.
For Annalise Bond, a graduate student in the lab of Meghan Morrissey, University of California, Santa Barbara (UCSB), macrophages are “the professional eaters of our immune system.” Every minute of every day, macrophages somewhere in the body are gorging themselves to remove the cellular debris that builds up in our tissues and organs.
In this image, Bond caught several macrophages (green) doing what they do best: shoveling it in—in this case, during a lab experiment. The macrophages are consuming silica beads (purple) prepared with biochemicals that whet their appetites. Each bead measures about five microns in diameter. That’s roughly the size of a bacterium or a spent red blood cell—debris that a macrophage routinely consumes.
When Bond snapped this image, she noticed a pattern that reminded her of a childhood tabletop game called Hungry Hungry Hippos. Kids press a lever attached to the mouth of a plastic hippo, its lower jaw flaps open, and the challenge is to fill the mouth with as many marbles as possible . . . just like the macrophages eating beads.
Bond adjusted the colors in the photo to make them pop. She then entered it into UCSB’s 2023 Art of Science contest with the caption of Hungry Hungry Macrophages, winning high marks for drawing the association.
Though the caption was written in fun, Bond studies in earnest a fascinating biological question: How do macrophages know what to eat in the body and what to leave untouched?
In her studies, Bond coats the silica beads shown above with a lipid bilayer to mimic a cell membrane. To that coating, she adds various small molecules and proteins as “eat-me” signals often found on the surface of dying cells. Some of the signals are well characterized; but many aren’t, meaning there’s still a lot to learn about what makes a macrophage “particularly hungry” and what makes a particular target cell “extra tasty.”
Capturing fluorescent images of macrophages under the microscope, Bond counts up how many beads are eaten. Beads bearing no signal to stimulate their appetite might get eaten occasionally. But when an especially enticing signal is added, macrophages will gorge themselves until they can’t eat anymore.
In the experiment pictured above, the beads contain the antibody immunoglobulin G (IgG), which tags foreign pathogens for macrophage removal. Interestingly, IgG antibody responses also play an important role in cancer immunotherapies, in which the immune system is unleashed to fight cancer.
Among its many areas of study, the NIH-supported Morrissey lab’s wants to understand better how macrophages interact with cancer cells. They want to learn how to make cancer cells even tastier to macrophages and program their elimination from the body. Sorting out the signals will be challenging, but we know that macrophages will take a bite at the right ones. They are, after all, professional eaters.
Links:
Cancer Immunotherapy (NIH)
Annalise Bond (University of California, Santa Barbara)
Morrissey Lab (University of California, Santa Barbara)
Art of Science (University of California, Santa Barbara)
NIH Support: National Institute of General Medical Sciences
Millions of Single-Cell Analyses Yield Most Comprehensive Human Cell Atlas Yet
Posted on by Lawrence Tabak, D.D.S., Ph.D.
There are 37 trillion or so cells in our bodies that work together to give us life. But it may surprise you that we still haven’t put a good number on how many distinct cell types there are within those trillions of cells.
That’s why in 2016, a team of researchers from around the globe launched a historic project called the Human Cell Atlas (HCA) consortium to identify and define the hundreds of presumed distinct cell types in our bodies. Knowing where each cell type resides in the body, and which genes each one turns on or off to create its own unique molecular identity, will revolutionize our studies of human biology and medicine across the board.
Since its launch, the HCA has progressed rapidly. In fact, it has already reached an important milestone with the recent publication in the journal Science of four studies that, together, comprise the first multi-tissue drafts of the human cell atlas. This draft, based on analyses of millions of cells, defines more than 500 different cell types in more than 30 human tissues. A second draft, with even finer definition, is already in the works.
Making the HCA possible are recent technological advances in RNA sequencing. RNA sequencing is a topic that’s been mentioned frequently on this blog in a range of research areas, from neuroscience to skin rashes. Researchers use it to detect and analyze all the messenger RNA (mRNA) molecules in a biological sample, in this case individual human cells from a wide range of tissues, organs, and individuals who voluntarily donated their tissues.
By quantifying these RNA messages, researchers can capture the thousands of genes that any given cell actively expresses at any one time. These precise gene expression profiles can be used to catalogue cells from throughout the body and understand the important similarities and differences among them.
In one of the published studies, funded in part by the NIH, a team co-led by Aviv Regev, a founding co-chair of the consortium at the Broad Institute of MIT and Harvard, Cambridge, MA, established a framework for multi-tissue human cell atlases [1]. (Regev is now on leave from the Broad Institute and MIT and has recently moved to Genentech Research and Early Development, South San Francisco, CA.)
Among its many advances, Regev’s team optimized single-cell RNA sequencing for use on cell nuclei isolated from frozen tissue. This technological advance paved the way for single-cell analyses of the vast numbers of samples that are stored in research collections and freezers all around the world.
Using their new pipeline, Regev and team built an atlas including more than 200,000 single-cell RNA sequence profiles from eight tissue types collected from 16 individuals. These samples were archived earlier by NIH’s Genotype-Tissue Expression (GTEx) project. The team’s data revealed unexpected differences among cell types but surprising similarities, too.
For example, they found that genetic profiles seen in muscle cells were also present in connective tissue cells in the lungs. Using novel machine learning approaches to help make sense of their data, they’ve linked the cells in their atlases with thousands of genetic diseases and traits to identify cell types and genetic profiles that may contribute to a wide range of human conditions.
By cross-referencing 6,000 genes previously implicated in causing specific genetic disorders with their single-cell genetic profiles, they identified new cell types that may play unexpected roles. For instance, they found some non-muscle cells that may play a role in muscular dystrophy, a group of conditions in which muscles progressively weaken. More research will be needed to make sense of these fascinating, but vital, discoveries.
The team also compared genes that are more active in specific cell types to genes with previously identified links to more complex conditions. Again, their data surprised them. They identified new cell types that may play a role in conditions such as heart disease and inflammatory bowel disease.
Two of the other papers, one of which was funded in part by NIH, explored the immune system, especially the similarities and differences among immune cells that reside in specific tissues, such as scavenging macrophages [2,3] This is a critical area of study. Most of our understanding of the immune system comes from immune cells that circulate in the bloodstream, not these resident macrophages and other immune cells.
These immune cell atlases, which are still first drafts, already provide an invaluable resource toward designing new treatments to bolster immune responses, such as vaccines and anti-cancer treatments. They also may have implications for understanding what goes wrong in various autoimmune conditions.
Scientists have been working for more than 150 years to characterize the trillions of cells in our bodies. Thanks to this timely effort and its advances in describing and cataloguing cell types, we now have a much better foundation for understanding these fundamental units of the human body.
But the latest data are just the tip of the iceberg, with vast flows of biological information from throughout the human body surely to be released in the years ahead. And while consortium members continue making history, their hard work to date is freely available to the scientific community to explore critical biological questions with far-reaching implications for human health and disease.
References:
[1] Single-nucleus cross-tissue molecular reference maps toward understanding disease gene function. Eraslan G, Drokhlyansky E, Anand S, Fiskin E, Subramanian A, Segrè AV, Aguet F, Rozenblatt-Rosen O, Ardlie KG, Regev A, et al. Science. 2022 May 13;376(6594):eabl4290.
[2] Cross-tissue immune cell analysis reveals tissue-specific features in humans. Domínguez Conde C, Xu C, Jarvis LB, Rainbow DB, Farber DL, Saeb-Parsy K, Jones JL,Teichmann SA, et al. Science. 2022 May 13;376(6594):eabl5197.
[3] Mapping the developing human immune system across organs. Suo C, Dann E, Goh I, Jardine L, Marioni JC, Clatworthy MR, Haniffa M, Teichmann SA, et al. Science. 2022 May 12:eabo0510.
Links:
Ribonucleic acid (RNA) (National Human Genome Research Institute/NIH)
Studying Cells (National Institute of General Medical Sciences/NIH)
Regev Lab (Broad Institute of MIT and Harvard, Cambridge, MA)
NIH Support: Common Fund; National Cancer Institute; National Human Genome Research Institute; National Heart, Lung, and Blood Institute; National Institute on Drug Abuse; National Institute of Mental Health; National Institute on Aging; National Institute of Allergy and Infectious Diseases; National Institute of Neurological Disorders and Stroke; National Eye Institute
How Severe COVID-19 Can Tragically Lead to Lung Failure and Death
Posted on by Dr. Francis Collins
More than 3 million people around the world, now tragically including thousands every day in India, have lost their lives to severe COVID-19. Though incredible progress has been made in a little more than a year to develop effective vaccines, diagnostic tests, and treatments, there’s still much we don’t know about what precisely happens in the lungs and other parts of the body that leads to lethal outcomes.
Two recent studies in the journal Nature provide some of the most-detailed analyses yet about the effects on the human body of SARS-CoV-2, the coronavirus that causes COVID-19 [1,2]. The research shows that in people with advanced infections, SARS-CoV-2 often unleashes a devastating series of host events in the lungs prior to death. These events include runaway inflammation and rampant tissue destruction that the lungs cannot repair.
Both studies were supported by NIH. One comes from a team led by Benjamin Izar, Columbia University, New York. The other involves a group led by Aviv Regev, now at Genentech, and formerly at Broad Institute of MIT and Harvard, Cambridge, MA.
Each team analyzed samples of essential tissues gathered from COVID-19 patients shortly after their deaths. Izar’s team set up a rapid autopsy program to collect and freeze samples within hours of death. He and his team performed single-cell RNA sequencing on about 116,000 cells from the lung tissue of 19 men and women. Similarly, Regev’s team developed an autopsy biobank that included 420 total samples from 11 organ systems, which were used to generate multiple single-cell atlases of tissues from the lung, kidney, liver, and heart.
Izar’s team found that the lungs of people who died of COVID-19 were filled with immune cells called macrophages. While macrophages normally help to fight an infectious virus, they seemed in this case to produce a vicious cycle of severe inflammation that further damaged lung tissue. The researchers also discovered that the macrophages produced high levels of IL-1β, a type of small inflammatory protein called a cytokine. This suggests that drugs to reduce effects of IL-1β might have promise to control lung inflammation in the sickest patients.
As a person clears and recovers from a typical respiratory infection, such as the flu, the lung repairs the damage. But in severe COVID-19, both studies suggest this isn’t always possible. Not only does SARS-CoV-2 destroy cells within air sacs, called alveoli, that are essential for the exchange of oxygen and carbon dioxide, but the unchecked inflammation apparently also impairs remaining cells from repairing the damage. In fact, the lungs’ regenerative cells are suspended in a kind of reparative limbo, unable to complete the last steps needed to replace healthy alveolar tissue.
In both studies, the lung tissue also contained an unusually large number of fibroblast cells. Izar’s team went a step further to show increased numbers of a specific type of pathological fibroblast, which likely drives the rapid lung scarring (pulmonary fibrosis) seen in severe COVID-19. The findings point to specific fibroblast proteins that may serve as drug targets to block deleterious effects.
Regev’s team also describes how the virus affects other parts of the body. One surprising discovery was there was scant evidence of direct SARS-CoV-2 infection in the liver, kidney, or heart tissue of the deceased. Yet, a closer look heart tissue revealed widespread damage, documenting that many different coronary cell types had altered their genetic programs. It’s still to be determined if that’s because the virus had already been cleared from the heart prior to death. Alternatively, the heart damage might not be caused directly by SARS-CoV-2, and may arise from secondary immune and/or metabolic disruptions.
Together, these two studies provide clearer pictures of the pathology in the most severe and lethal cases of COVID-19. The data from these cell atlases has been made freely available for other researchers around the world to explore and analyze. The hope is that these vast data sets, together with future analyses and studies of people who’ve tragically lost their lives to this pandemic, will improve our understanding of long-term complications in patients who’ve survived. They also will now serve as an important foundational resource for the development of promising therapies, with the goal of preventing future complications and deaths due to COVID-19.
References:
[1] A molecular single-cell lung atlas of lethal COVID-19. Melms JC, Biermann J, Huang H, Wang Y, Nair A, Tagore S, Katsyv I, Rendeiro AF, Amin AD, Schapiro D, Frangieh CJ, Luoma AM, Filliol A, Fang Y, Ravichandran H, Clausi MG, Alba GA, Rogava M, Chen SW, Ho P, Montoro DT, Kornberg AE, Han AS, Bakhoum MF, Anandasabapathy N, Suárez-Fariñas M, Bakhoum SF, Bram Y, Borczuk A, Guo XV, Lefkowitch JH, Marboe C, Lagana SM, Del Portillo A, Zorn E, Markowitz GS, Schwabe RF, Schwartz RE, Elemento O, Saqi A, Hibshoosh H, Que J, Izar B. Nature. 2021 Apr 29.
[2] COVID-19 tissue atlases reveal SARS-CoV-2 pathology and cellular targets. Delorey TM, Ziegler CGK, Heimberg G, Normand R, Shalek AK, Villani AC, Rozenblatt-Rosen O, Regev A. et al. Nature. 2021 Apr 29.
Links:
COVID-19 Research (NIH)
Izar Lab (Columbia University, New York)
Aviv Regev (Genentech, South San Francisco, CA)
NIH Support: National Center for Advancing Translational Sciences; National Heart, Lung, and Blood Institute; National Cancer Institute; National Institute of Allergy and Infectious Diseases; National Institute of Diabetes and Digestive and Kidney Diseases; National Human Genome Research Institute; National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism
First Molecular Profiles of Severe COVID-19 Infections
Posted on by Dr. Francis Collins
To ensure that people with coronavirus disease 2019 (COVID-19) get the care they need, it would help if a simple blood test could predict early on which patients are most likely to progress to severe and life-threatening illness—and which are more likely to recover without much need for medical intervention. Now, researchers have provided some of the first evidence that such a test might be possible.
This tantalizing possibility comes from a study reported recently in the journal Cell. In this study, researchers took blood samples from people with mild to severe COVID-19 and analyzed them for nearly 2,000 proteins and metabolites [1]. Their detailed analyses turned up hundreds of molecular changes in blood that differentiated milder COVID-19 symptoms from more severe illness. What’s more, they found that they could train a computer to use the most informative of the proteins and predict the disease severity with a high degree of accuracy.
The findings come from the lab of Tiannan Guo, Westlake University, Zhejiang Province, China. His team recognized that, while we’ve learned a lot about the clinical symptoms of COVID-19 and the spread of the illness around the world, much less is known about the condition’s underlying molecular features. It also remains mysterious what distinguishes the 80 percent of symptomatic infected people who recover with little to no need for medical care from the other 20 percent, who suffer from much more serious illness, including respiratory distress requiring oxygen or even more significant medical interventions.
In search of clues, Guo and colleagues analyzed hundreds of molecular changes in blood samples collected from 53 healthy people and 46 people with COVID-19, including 21 with severe disease involving respiratory distress and decreased blood-oxygen levels. Their studies turned up more than 470 proteins and metabolites that differed in people with COVID-19 compared to healthy people. Of those, levels of about 300 were associated with disease severity.
Further analysis revealed that the majority of proteins and metabolites on the list are associated with the suppression or dysregulation of one of three biological processes. Two processes are related to the immune system, including early immune responses and the function of particular scavenging immune cells called macrophages. The third relates to the function of platelets, which are sticky, disc-shaped cell fragments that play an essential role in blood clotting. Such biological insights might help pave the way for potentially effective new ways to treat COVID-19 down the road.
Next, the researchers turned to “machine learning” to explore the possibility that such molecular changes also might be used to predict mild versus severe COVID-19. Machine learning involves the use of computers to discern patterns, or molecular signatures, in large data sets that a human being couldn’t readily pick out. In this case, the question was whether the computer could “learn” to tell the difference between mild and severe COVID-19 based on molecular data alone.
Their analyses showed that a computer, once trained, could differentiate mild and severe COVID-19 based on just 22 proteins and 7 metabolites. Their model correctly classified all but one person in the original training set, for an accuracy of about 94 percent. And importantly, in further prospective validation tests, they confirmed that this model accurately identified mild versus severe COVID-19 in most cases.
While these findings are certainly encouraging, there’s much more work to do. It will be important to explore these molecular signatures in many more people. It also will be critical to find out how early in the course of the disease such telltale signatures arise. While we await those answers, I find encouragement in all that we’re learning—and will continue to learn—about COVID-19 each day.
Reference:
[1] Proteomic and metabolomic characterization of COVID-19 patient sera. Shen B et al. Cell. 28 May 2020. [Epub ahead of publication]
Links:
Coronavirus (COVID-19) (NIH)
Blood Tests (National Heart, Lung, and Blood Institute/NIH)
Tiannan Guo Lab (Westlake University, Zhejiang Province, China)
Working to Improve Immunotherapy for Lung Cancer
Posted on by Dr. Francis Collins
For those who track cancer statistics, this year started off on a positive note with word that lung cancer deaths continue to decline in the United States [1]. While there’s plenty of credit to go around for that encouraging news—and continued reduction in smoking is a big factor—some of this progress likely can be ascribed to a type of immunotherapy, called PD-1 inhibitors. This revolutionary approach has dramatically changed the treatment landscape for the most common type of lung cancer, non-small cell lung cancer (NSCLC).
PD-1 inhibitors, which have only been available for about five years, prime one component of a patient’s own immune system, called T cells, to seek and destroy malignant cells in the lungs. Unfortunately, however, only about 20 percent of people with NSCLC respond to PD-1 inhibitors. So, many researchers, including the team of A. McGarry Houghton, Fred Hutchinson Cancer Research Center, Seattle, are working hard to extend the benefits of immunotherapy to more cancer patients.
The team’s latest paper, published in JCI Insight [2], reveals that one culprit behind a poor response to immunotherapy may be the immune system’s own first responders: neutrophils. Billions of neutrophils circulate throughout the body to track down abnormalities, such as harmful bacteria and malignant cells. They also contact other parts of the immune system, including T cells, if help is needed to eliminate the health threat.
In their study, the Houghton team, led by Julia Kargl, combined several lab techniques to take a rigorous, unbiased look at the immune cell profiles of tumor samples from dozens of NSCLC patients who received PD-1 inhibitors as a frontline treatment. The micrographs above show tumor samples from two of these patients.
In the image on the left, large swaths of T cells (light blue) have infiltrated the cancer cells (white specks). Interestingly, other immune cells, including neutrophils (magenta), are sparse.
In contrast, in the image on the right, T cells (light blue) are sparse. Instead, the tumor teems with other types of immune cells, including macrophages (red), two types of monocytes (yellow, green), and, most significantly, lots of neutrophils (magenta). These cells arise from myeloid progenitor cells in the bone marrow, while T cells arise from the marrow’s lymphoid progenitor cell.
Though the immune profiles of some tumor samples were tough to classify, the researchers found that most fit neatly into two subgroups: tumors showing active levels of T cell infiltration (like the image on the left) or those with large numbers of myeloid immune cells, especially neutrophils (like the image on the right). This dichotomy then served as a reliable predictor of treatment outcome. In the tumor samples with majority T cells, the PD-1 inhibitor worked to varying degrees. But in the tumor samples with predominantly neutrophil infiltration, the treatment failed.
Houghton’s team has previously found that many cancers, including NSCLC, actively recruit neutrophils, turning them into zombie-like helpers that falsely signal other immune cells, like T cells, to stay away. Based on this information, Houghton and colleagues used a mouse model of lung cancer to explore a possible way to increase the success rate of PD-1 immunotherapy.
In their mouse experiments, the researchers found that when PD-1 was combined with an existing drug that inhibits neutrophils, lung tumors infiltrated with neutrophils were converted into tumors infiltrated by T cells. The tumors treated with the combination treatment also expressed genes associated with an active immunotherapy response.
This year, January brought encouraging news about decreasing deaths from lung cancer. But with ongoing basic research, like this study, to tease out the mechanisms underlying the success and failure of immunotherapy, future months may bring even better news.
References:
[1] Cancer statistics, 2020. Siegel RL, Miller KD, Jemal A. CA Cancer J Clin. 2020 Jan;70(1):7-30.
[2] Neutrophil content predicts lymphocyte depletion and anti-PD1 treatment failure in NSCLC. Kargl J, Zhu X, Zhang H, Yang GHY, Friesen TJ, Shipley M, Maeda DY, Zebala JA, McKay-Fleisch J, Meredith G, Mashadi-Hossein A, Baik C, Pierce RH, Redman MW, Thompson JC, Albelda SM, Bolouri H, Houghton AM. JCI Insight. 2019 Dec 19;4(24).
[3] Neutrophils dominate the immune cell composition in non-small cell lung cancer. Kargl J, Busch SE, Yang GH, Kim KH, Hanke ML, Metz HE, Hubbard JJ, Lee SM, Madtes DK, McIntosh MW, Houghton AM. Nat Commun. 2017 Feb 1;8:14381.
Links:
Non-Small Cell Lung Cancer Treatment (PDQ®)–Patient Version (National Cancer Institute/NIH)
Spotlight on McGarry Houghton (Fred Hutchinson Cancer Research Center, Seattle)
Houghton Lab (Fred Hutchinson Cancer Research Center)
NIH Support: National Cancer Institute
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