14.2.1: Architecture of the Immune System - Biology

14.2.1: Architecture of the Immune System - Biology

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Learning Objectives

  • Define memory, primary response, secondary response, and specificity
  • Distinguish between humoral and cellular immunity
  • Differentiate between antigens, epitopes, and haptens
  • Describe the structure and function of antibodies and distinguish between the different classes of antibodies

Clinical Focus: Part 1

Olivia, a one-year old infant, is brought to the emergency room by her parents, who report her symptoms: excessive crying, irritability, sensitivity to light, unusual lethargy, and vomiting. A physician feels swollen lymph nodes in Olivia’s throat and armpits. In addition, the area of the abdomen over the spleen is swollen and tender.

Exercise (PageIndex{1})

  1. What do these symptoms suggest?
  2. What tests might be ordered to try to diagnose the problem?

Adaptive immunity is defined by two important characteristics: specificity and memory. Specificity refers to the adaptive immune system’s ability to target specific pathogens, and memory refers to its ability to quickly respond to pathogens to which it has previously been exposed. For example, when an individual recovers from chickenpox, the body develops a memory of the infection that will specifically protect it from the causative agent, the varicella-zoster virus, if it is exposed to the virus again later.

Specificity and memory are achieved by essentially programming certain cells involved in the immune response to respond rapidly to subsequent exposures of the pathogen. This programming occurs as a result of the first exposure to a pathogen or vaccine, which triggers a primary response. Subsequent exposures result in a secondary response that is faster and stronger as a result of the body’s memory of the first exposure (Figure (PageIndex{1})). This secondary response, however, is specific to the pathogen in question. For example, exposure to one virus (e.g., varicella-zoster virus) will not provide protection against other viral diseases (e.g., measles, mumps, or polio).

Adaptive specific immunity involves the actions of two distinct cell types: B lymphocytes (B cells) and T lymphocytes(T cells). Although B cells and T cells arise from a common hematopoietic stem cell differentiation pathway, their sites of maturation and their roles in adaptive immunity are very different.

B cells mature in the bone marrow and are responsible for the production of glycoproteins called antibodies, or immunoglobulins. Antibodies are involved in the body’s defense against pathogens and toxins in the extracellular environment. Mechanisms of adaptive specific immunity that involve B cells and antibody production are referred to as humoral immunity. The maturation of T cells occurs in the thymus. T cells function as the central orchestrator of both innate and adaptive immune responses. They are also responsible for destruction of cells infected with intracellular pathogens. The targeting and destruction of intracellular pathogens by T cells is called cell-mediated immunity, or cellular immunity.

Exercise (PageIndex{2})

  1. List the two defining characteristics of adaptive immunity.
  2. Explain the difference between a primary and secondary immune response.
  3. How do humoral and cellular immunity differ?


Activation of the adaptive immune defenses is triggered by pathogen-specific molecular structures called antigens. Antigens are similar to the pathogen-associated molecular patterns (PAMPs) discussed in Pathogen Recognition and Phagocytosis; however, whereas PAMPs are molecular structures found on numerous pathogens, antigens are unique to a specific pathogen. The antigens that stimulate adaptive immunity to chickenpox, for example, are unique to the varicella-zoster virus but significantly different from the antigens associated with other viral pathogens.

The term antigen was initially used to describe molecules that stimulate the production of antibodies; in fact, the term comes from a combination of the words antibody and generator, and a molecule that stimulates antibody production is said to be antigenic. However, the role of antigens is not limited to humoral immunity and the production of antibodies; antigens also play an essential role in stimulating cellular immunity, and for this reason antigens are sometimes more accurately referred to as immunogens. In this text, however, we will typically refer to them as antigens.

Pathogens possess a variety of structures that may contain antigens. For example, antigens from bacterial cells may be associated with their capsules, cell walls, fimbriae, flagella, or pili. Bacterial antigens may also be associated with extracellular toxins and enzymes that they secrete. Viruses possess a variety of antigens associated with their capsids, envelopes, and the spike structures they use for attachment to cells.

Antigens may belong to any number of molecular classes, including carbohydrates, lipids, nucleic acids, proteins, and combinations of these molecules. Antigens of different classes vary in their ability to stimulate adaptive immune defenses as well as in the type of response they stimulate (humoral or cellular). The structural complexity of an antigenic molecule is an important factor in its antigenic potential. In general, more complex molecules are more effective as antigens. For example, the three-dimensional complex structure of proteins make them the most effective and potent antigens, capable of stimulating both humoral and cellular immunity. In comparison, carbohydrates are less complex in structure and therefore less effective as antigens; they can only stimulate humoral immune defenses. Lipids and nucleic acids are the least antigenic molecules, and in some cases may only become antigenic when combined with proteins or carbohydrates to form glycolipids, lipoproteins, or nucleoproteins.

One reason the three-dimensional complexity of antigens is so important is that antibodies and T cells do not recognize and interact with an entire antigen but with smaller exposed regions on the surface of antigens called epitopes. A single antigen may possess several different epitopes (Figure (PageIndex{2})), and different antibodies may bind to different epitopes on the same antigen (Figure (PageIndex{3})). For example, the bacterial flagellum is a large, complex protein structure that can possess hundreds or even thousands of epitopes with unique three-dimensional structures. Moreover, flagella from different bacterial species (or even strains of the same species) contain unique epitopes that can only be bound by specific antibodies.

An antigen’s size is another important factor in its antigenic potential. Whereas large antigenic structures like flagella possess multiple epitopes, some molecules are too small to be antigenic by themselves. Such molecules, called haptens, are essentially free epitopes that are not part of the complex three-dimensional structure of a larger antigen. For a hapten to become antigenic, it must first attach to a larger carrier molecule (usually a protein) to produce a conjugate antigen. The hapten-specific antibodies produced in response to the conjugate antigen are then able to interact with unconjugated free hapten molecules. Haptens are not known to be associated with any specific pathogens, but they are responsible for some allergic responses. For example, the hapten urushiol, a molecule found in the oil of plants that cause poison ivy, causes an immune response that can result in a severe rash (called contact dermatitis). Similarly, the hapten penicillin can cause allergic reactions to drugs in the penicillin class.

Exercise (PageIndex{3})

  1. What is the difference between an antigen and an epitope?
  2. What factors affect an antigen’s antigenic potential?
  3. Why are haptens typically not antigenic, and how do they become antigenic?


Antibodies (also called immunoglobulins) are glycoproteins that are present in both the blood and tissue fluids. The basic structure of an antibody monomer consists of four protein chains held together by disulfide bonds (Figure (PageIndex{4})). A disulfide bond is a covalent bond between the sulfhydryl R groups found on two cysteine amino acids. The two largest chains are identical to each other and are called the heavy chains. The two smaller chains are also identical to each other and are called the light chains. Joined together, the heavy and light chains form a basic Y-shaped structure.

The two ‘arms’ of the Y-shaped antibody molecule are known as the Fab region, for “fragment of antigen binding.” The far end of the Fab region is the variable region, which serves as the site of antigen binding. The amino acid sequence in the variable region dictates the three-dimensional structure, and thus the specific three-dimensional epitope to which the Fab region is capable of binding. Although the epitope specificity of the Fab regions is identical for each arm of a single antibody molecule, this region displays a high degree of variability between antibodies with different epitope specificities. Binding to the Fab region is necessary for neutralization of pathogens, agglutination or aggregation of pathogens, and antibody-dependent cell-mediated cytotoxicity.

The constant region of the antibody molecule includes the trunk of the Y and lower portion of each arm of the Y. The trunk of the Y is also called the Fc region, for “fragment of crystallization,” and is the site of complement factor binding and binding to phagocytic cells during antibody-mediated opsonization.

Exercise (PageIndex{4})

Describe the different functions of the Fab region and the Fc region.

Antibody Classes

The constant region of an antibody molecule determines its class, or isotype. The five classes of antibodies are IgG, IgM, IgA, IgD, and IgE. Each class possesses unique heavy chains designated by Greek letters γ, μ, α, δ, and ε, respectively. Antibody classes also exhibit important differences in abundance in serum, arrangement, body sites of action, functional roles, and size (Figure (PageIndex{5})).

IgG is a monomer that is by far the most abundant antibody in human blood, accounting for about 80% of total serum antibody. IgG penetrates efficiently into tissue spaces, and is the only antibody class with the ability to cross the placental barrier, providing passive immunity to the developing fetus during pregnancy. IgG is also the most versatile antibody class in terms of its role in the body’s defense against pathogens.

IgM is initially produced in a monomeric membrane-bound form that serves as an antigen-binding receptor on B cells. The secreted form of IgM assembles into a pentamer with five monomers of IgM bound together by a protein structure called the J chain. Although the location of the J chain relative to the Fc regions of the five monomers prevents IgM from performing some of the functions of IgG, the ten available Fab sites associated with a pentameric IgM make it an important antibody in the body’s arsenal of defenses. IgM is the first antibody produced and secreted by B cells during the primary and secondary immune responses, making pathogen-specific IgM a valuable diagnostic marker during active or recent infections.

IgA accounts for about 13% of total serum antibody, and secretory IgA is the most common and abundant antibody class found in the mucus secretions that protect the mucous membranes. IgA can also be found in other secretions such as breast milk, tears, and saliva. Secretory IgA is assembled into a dimeric form with two monomers joined by a protein structure called the secretory component. One of the important functions of secretory IgA is to trap pathogens in mucus so that they can later be eliminated from the body.

Similar to IgM, IgD is a membrane-bound monomer found on the surface of B cells, where it serves as an antigen-binding receptor. However, IgD is not secreted by B cells, and only trace amounts are detected in serum. These trace amounts most likely come from the degradation of old B cells and the release of IgD molecules from their cytoplasmic membranes.

IgE is the least abundant antibody class in serum. Like IgG, it is secreted as a monomer, but its role in adaptive immunity is restricted to anti-parasitic defenses. The Fc region of IgE binds to basophils and mast cells. The Fab region of the bound IgE then interacts with specific antigen epitopes, causing the cells to release potent pro-inflammatory mediators. The inflammatory reaction resulting from the activation of mast cells and basophils aids in the defense against parasites, but this reaction is also central to allergic reactions (see Diseases of the Immune System.)

Exercise (PageIndex{5})

  1. What part of an antibody molecule determines its class?
  2. What class of antibody is involved in protection against parasites?
  3. Describe the difference in structure between IgM and IgG.

Antigen-Antibody Interactions

Different classes of antibody play important roles in the body’s defense against pathogens. These functions include neutralization of pathogens, opsonization for phagocytosis, agglutination, complement activation, and antibody-dependent cell-mediated cytotoxicity. For most of these functions, antibodies also provide an important link between adaptive specific immunity and innate nonspecific immunity.

Neutralization involves the binding of certain antibodies (IgG, IgM, or IgA) to epitopes on the surface of pathogens or toxins, preventing their attachment to cells. For example, Secretory IgA can bind to specific pathogens and block initial attachment to intestinal mucosal cells. Similarly, specific antibodies can bind to certain toxins, blocking them from attaching to target cells and thus neutralizing their toxic effects. Viruses can be neutralized and prevented from infecting a cell by the same mechanism (Figure (PageIndex{6})).

As described in Chemical Defenses, opsonization is the coating of a pathogen with molecules, such as complementfactors, C-reactive protein, and serum amyloid A, to assist in phagocyte binding to facilitate phagocytosis. IgG antibodies also serve as excellent opsonins, binding their Fab sites to specific epitopes on the surface of pathogens. Phagocytic cells such as macrophages, dendritic cells, and neutrophils have receptors on their surfaces that recognize and bind to the Fc portion of the IgG molecules; thus, IgG helps such phagocytes attach to and engulf the pathogens they have bound (Figure (PageIndex{7})).

Agglutination or aggregation involves the cross-linking of pathogens by antibodies to create large aggregates (Figure (PageIndex{8})). IgG has two Fab antigen-binding sites, which can bind to two separate pathogen cells, clumping them together. When multiple IgG antibodies are involved, large aggregates can develop; these aggregates are easier for the kidneys and spleen to filter from the blood and easier for phagocytes to ingest for destruction. The pentameric structure of IgMprovides ten Fab binding sites per molecule, making it the most efficient antibody for agglutination.

Another important function of antibodies is activation of the complement cascade. As discussed in the previous chapter, the complement system is an important component of the innate defenses, promoting the inflammatory response, recruiting phagocytes to site of infection, enhancing phagocytosis by opsonization, and killing gram-negative bacterial pathogens with the membrane attack complex (MAC). Complement activation can occur through three different pathways (see [link]), but the most efficient is the classical pathway, which requires the initial binding of IgG or IgM antibodies to the surface of a pathogen cell, allowing for recruitment and activation of the C1 complex.

Yet another important function of antibodies is antibody-dependent cell-mediated cytotoxicity (ADCC), which enhances killing of pathogens that are too large to be phagocytosed. This process is best characterized for natural killer cells (NK cells), as shown in Figure (PageIndex{9}), but it can also involve macrophages and eosinophils. ADCC occurs when the Fab region of an IgG antibody binds to a large pathogen; Fc receptors on effector cells (e.g., NK cells) then bind to the Fc region of the antibody, bringing them into close proximity with the target pathogen. The effector cell then secretes powerful cytotoxins (e.g., perforin and granzymes) that kill the pathogen.

Exercise (PageIndex{6})

  1. Where is IgA normally found?
  2. Which class of antibody crosses the placenta, providing protection to the fetus?
  3. Compare the mechanisms of opsonization and antibody-dependent cell-mediated cytotoxicity.

Key Concepts and Summary

  • Adaptive immunity is an acquired defense against foreign pathogens that is characterized by specificity and memory. The first exposure to an antigen stimulates a primary response, and subsequent exposures stimulate a faster and strong secondary response.
  • Adaptive immunity is a dual system involving humoral immunity (antibodies produced by B cells) and cellular immunity (T cells directed against intracellular pathogens).
  • Antigens, also called immunogens, are molecules that activate adaptive immunity. A single antigen possesses smaller epitopes, each capable of inducing a specific adaptive immune response.
  • An antigen’s ability to stimulate an immune response depends on several factors, including its molecular class, molecular complexity, and size.
  • Antibodies (immunoglobulins) are Y-shaped glycoproteins with two Fab sites for binding antigens and an Fc portion involved in complement activation and opsonization.
  • The five classes of antibody are IgM, IgG, IgA, IgE, and IgD, each differing in size, arrangement, location within the body, and function. The five primary functions of antibodies are neutralization, opsonization, agglutination, complement activation, and antibody-dependent cell-mediated cytotoxicity (ADCC).

Multiple Choice

Antibodies are produced by ________.

A. plasma cells
B. T cells
C. bone marrow
D. B cells


Cellular adaptive immunity is carried out by ________.

A. B cells
B. neutrophils


A single antigen molecule may be composed of many individual ________.

A. T-cell receptors
B. B-cell receptors
D. epitopes


Which class of molecules is the most antigenic?

A. polysaccharides
B. lipids
C. proteins
D. carbohydrates



Match the antibody class with its description.

___IgAA. This class of antibody is the only one that can cross the placenta.
___IgDB. This class of antibody is the first to appear after activation of B cells.
___IgEC. This class of antibody is involved in the defense against parasitic infections and involved in allergic responses.
___IgGD. This class of antibody is found in very large amounts in mucus secretions.
___IgME. This class of antibody is not secreted by B cells but is expressed on the surface of naïve B cells.

d, e, c, a, b

Fill in the Blank

There are two critically important aspects of adaptive immunity. The first is specificity, while the second is ________.


________ immunity involves the production of antibody molecules that bind to specific antigens.


The heavy chains of an antibody molecule contain ________ region segments, which help to determine its class or isotype.


The variable regions of the heavy and light chains form the ________ sites of an antibody.


Short Answer

What is the difference between humoral and cellular adaptive immunity?

What is the difference between an antigen and a hapten?

Describe the mechanism of antibody-dependent cell-mediated cytotoxicity.

Immune response in COVID-19: A review

The immune system protects against viruses and diseases and produces antibodies to kill pathogens. This review presents a brief overview of the immune system regarding its protection of the human body from COVID-19 illustrates the process of the immune system, how it works, and its mechanism to fight virus and presents information on the most recent COVID-19 treatments and experimental data. Various types of potential challenges for the immunes system are also discussed. At the end of the article, foods to consume and avoid are suggested, and physical exercise is encouraged. This article can be used worldwide as a state of the art in this critical moment for promising alternative solutions related to surviving the coronavirus.

Immune responses to adenovirus and adeno-associated vectors used for gene therapy of brain diseases: the role of immunological synapses in understanding the cell biology of neuroimmune interactions

Researchers have conducted numerous pre-clinical and clinical gene transfer studies using recombinant viral vectors derived from a wide range of pathogenic viruses such as adenovirus, adeno-associated virus, and lentivirus. As viral vectors are derived from pathogenic viruses, they have an inherent ability to induce a vector specific immune response when used in vivo. The role of the immune response against the viral vector has been implicated in the inconsistent and unpredictable translation of pre-clinical success into therapeutic efficacy in human clinical trials using gene therapy to treat neurological disorders. Herein we thoroughly examine the effects of the innate and adaptive immune responses on therapeutic gene expression mediated by adenoviral, AAV, and lentiviral vectors systems in both pre-clinical and clinical experiments. Furthermore, the immune responses against gene therapy vectors and the resulting loss of therapeutic gene expression are examined in the context of the architecture and neuroanatomy of the brain immune system. The chapter closes with a discussion of the relationship between the elimination of transgene expression and the in vivo immunological synapses between immune cells and target virally infected brain cells. Importantly, although systemic immune responses against viral vectors injected systemically has thought to be deleterious in a number of trials, results from brain gene therapy clinical trials do not support this general conclusion suggesting brain gene therapy may be safer from an immunological standpoint.


Fig. (1). Anti-adenoviral immune responses completely eliminate…

Fig. (1). Anti-adenoviral immune responses completely eliminate transgene expression from first generation adenoviral vectors

Fig. (2). Anti-adenoviral immune responses are incapable…

Fig. (2). Anti-adenoviral immune responses are incapable of eliminating transgene expression from HC-Ad vectors

Fig. (3). Comparison of pre-existing responses against…

Fig. (3). Comparison of pre-existing responses against first generation adenovirus, high capacity adenovirus, and transgene

Fig. (4). Pre-existing responses against AAV vectors

Fig. (4). Pre-existing responses against AAV vectors

Fig. (5). SMAC formation at immunological synapses…

Fig. (5). SMAC formation at immunological synapses in vivo , between T cells and infected…



Related Stories

When Carl F. Nathan, Microbiology and Immunology, Weill Cornell Medicine, received his acceptance to Harvard University Medical School in December 1966, he did not celebrate. Earlier that day, he had watched his mother die from cancer.

“I made an emotional and intellectual commitment to the field that day,” Nathan says. “I wanted to express my gratitude to her and try to pay back, too late, by helping other people in the same situation.”

Nathan went on to medical school, a residency, and an oncology fellowship, but he soon became frustrated with chemotherapy as the default, and usually ineffective, treatment at the time. Already torn between clinical oncology and fundamental research, Nathan saw that going to the root of the problem—to understand how the body’s immune system works—could uncover new approaches to combat not only cancer but infectious diseases as well.

The Immune System versus Bacteria

“The immune system has enormous destructive power,” says Nathan. “It can destroy any tissue it thinks is infected. But at that time, we didn’t know anything about what the firepower consisted of and how it was regulated.”

In 1977 Nathan began full-time research at The Rockefeller University to find out, looking specifically at immune response to infectious diseases. “I thought I could make faster progress using infectious disease,” he says, “because that was the situation in which these immune capacities evolved, whereas cancer typically afflicts people after their reproductive age.”

Nathan knew that neutrophils and macrophages were the cells of the immune system that could kill pathogens directly, rather than killing infected host cells. Over the next decade, he would discover that macrophages are activated by a protein, called interferon-gamma. Interferon-gamma is produced by T lymphocytes when they detect bacteria. His lab also found that, to his and others’ surprise, this activation enables the production of reactive oxygen species such as superoxide and hydrogen peroxide, which the cells then use as weapons against the bacteria.

“We were then able to introduce interferon-gamma as a treatment for children who were deficient in this system, who would have died from bacterial or fungal infections,” Nathan says. The treatment also worked for leprosy, which is caused by a mycobacterium. This pathway didn’t explain everything, however. “We were keenly aware that something was missing,” Nathan says.

When he moved to Cornell in 1986, he discovered the second major killing pathway. The immune response to infectious disease also included neutrophil and macrophage production of another protein, the enzyme iNOS (inducible nitric oxide synthase), which makes reactive nitrogen species—another weapon.

When both of these pathways were knocked out in mouse models, the result was not compatible with life in the wild. “They had the normal number of macrophages and neutrophils and could even mobilize them to infected sites, but the cells couldn’t kill the bacteria,” Nathan explains. “It is the most severe immunodeficient phenotype toward bacterial infections I know of with normal numbers of mobilized phagocytes, and it shows that these two systems are partly mutually redundant but collectively indispensable for going about daily life.”

Studying an Enduring Infectious Disease, Tuberculosis

Nathan and his team began testing to find which diseases thrived when the iNOS pathway was blocked. Tuberculosis—caused by Mycobacterium tuberculosis (Mtb)—the leading death-causing bacterial infection in the world, was at the top of the list.

“So I started learning about Mtb,” Nathan says, “and I realized there’s an enormous amount of human biology that Mtb is trying to teach us if we would listen to it.”

Scientists think that tuberculosis (TB) has been around for at least 70,000 years. Nathan says, “If we stop to think about that, we haven’t eliminated it, and it hasn’t eliminated us. So there’s some kind of equilibrium.”

“Mtb gets the immune system to destroy lung tissue, making us cough or sneeze. Then it takes a ride on little droplets—liquefied lung tissue.”

This is related to the pathogen’s lifecycle and that humans are its only natural host. “Before we lived in cities, it would have been really important for TB to not kill everyone in a village quickly before they had children,” Nathan explains, “because then there would be no new hosts.”

Mtb needs to take its time to cause overt disease. It also needs to be recognized by the immune system in order to infect new victims. “Mtb gets the immune system to destroy lung tissue, making us cough or sneeze,” Nathan explains. “Then it takes a ride on little droplets—liquefied lung tissue. “Mtb has to walk this tightrope,” he continues, “inciting our immunity but also titrating it, surviving it, and then exploiting it in order to get to the next host.”

This relationship spurs many questions: After being recognized by the immune system, how does Mtb survive? What are its defenses? “To me, it’s a textbook that tells us what human immunity brings to the battle,” says Nathan. In very broad terms, he and others have found seven strategies the bacteria use, from degrading the immune system’s chemistry, to repairing damage, to sequestering damage.

This work also brings Nathan 180 degrees from researching how the immune system kills bacteria to how the bacteria fight back. “The goal is to see it from both sides, and then maybe you can be the puppet master,” he says. “Then you have a chance to make the immune system more successful more of the time.”

Nathan has found enzymes that help Mtb carry out many of its defense mechanisms. He’s also found inhibitors of those enzymes. “But unfortunately that doesn’t mean we’ve found drugs,” he says.

Wanted: New Drugs for Tuberculosis

As Nathan learned more about Mtb, he became aware of another problem, one that has vast implications for global health—antimicrobial resistance. “I became alarmed, because the rise in resistance coincided with the retreat of most of the pharmaceutical industry from trying to make new antibiotics.”

Economics have played a role in this withdrawal, but Nathan says it’s also because companies were struggling to find new antibiotics. “The practices they used in the 1950s and ‘60s were so efficient that they turned into a dogma, a mind freeze,” he says. “Here’s where people who come to the problem from a different discipline might be able to bring new ways of thinking.”

While academics have often provided research and technology for industry, there have been few opportunities for side-by-side collaboration. Nathan, with many others, is working to break down the boundaries. “Now we’re working with industry partners from the very beginning,” he says. “This arm-in-arm collaboration is incredibly efficient, and when you come to the inevitable problems, you have a whole multidisciplinary team to think about it.”

Nathan is involved in three projects that support the collaboration of academics and industry colleagues: the Bill and Melinda Gates Foundation’s TB Drug Accelerator program, the Tri-Institutional Therapeutics Discovery Institute, and Tres Cantos Open Lab. Nathan is also principal investigator for a seven-year grant from the National Institute of Allergy and Infectious Disease (NIAID), which brings six institutions, five Weill Cornell Medicine labs, and industry partners together in a TB Research Unit. Contributions from the NIAID could reach $46 million.

To these endeavors, Nathan is contributing his new understanding of Mtb, including what he’s learned about its defenses and the enzymes involved. “But there’s a big learning curve,” he says. “Drug discovery is full of failure, and I’ve been learning how many ways there are to fail.”

Compounds that Nathan has had high hopes for end up being toxic in some way or don’t work for inexplicable reasons. “But there’s enormous enthusiasm about the next group of compounds, so we spring back up,” he says. “I don’t think you can last this long in science if you can’t get up when you’ve been knocked down.”

Through the joys and disappointments, Nathan is always driving forward. “It’s a thrill to discover something that answers a question you didn’t even know you were asking,” he says. “It’s a thrill to see people in my lab bring their own insights and launch their own paths. But we haven’t succeeded nearly well enough yet. We have so much farther to go.”

Курс 2

Fundamentals of Immunology: T Cells and Signaling

Course 2 of a three course specialization called Fundamentals of Immunology. Each course in the specialization presents material that builds on the previous course's material.

This is the second half of the journey through the defenses your body uses to keep you healthy. In the first part we learned about innate immunity and B cell function. The second part covers T cell function and coordination of the immune response. Fundamentals of Immunology: T cells and Signaling builds on the first course to describe the functions of Complement, MHC presentation to T cells, T cell development and signaling. The early lectures survey cells, tissues and organs using metaphors, cartoons and models to improve understanding and retention. This course includes the structure of both MHC proteins and T cell receptors and the sources of variation. The course provides animations of gene rearrangement, developmental processes and signal cascades. Testing employs multiple choice questions testing facts, concepts, and application of principles. Questions may refer to diagrams, drawing and photographs used in lecture and reproduced in the outline. What You’ll Learn: How complement uses adaptive and innate triggers to target pathogens. The detailed structure and coding of MHC proteins and both alpha-beta and gamma delta receptors and how these proteins interact to initiate an adaptive immune response. The basics of signaling, and the varieties of external receipt and internal activation pathways. We bine the process of putting together how signals and crosstalk control the activity of the immune system.

Materials and methods

Animals and challenge infections

Female BALB/c mice were purchased from Harlan Olac (Bicester, UK). DO11.10 mice, with CD4 + T cells specific for the OVA323-339 peptide in the context of the MHC class II molecule I-A d recognized by the KJ1.26 clonotypic antibody [96] were obtained originally from N. Lycke, University of Göteborg, Sweden. MD4 mice containing HEL-specific B cells [51] were backcrossed onto the BALB/c background. All mice were maintained at Biological Services, University of Glasgow, under specific pathogen-free conditions and first used between 6 and 8 weeks of age in accordance with local and UK Home Office regulations.

To initiate a malaria infection, mice were inoculated with 1 × 10 6 P. chabaudi AS-infected erythrocytes intra-peritoneally. Parasitemia was monitored by thin blood smears stained with Giemsa's stain. Peak parasitemia occurred at 5-6 days post-infection, after which time parasite levels declined and remained at low but usually detectable levels for the remainder of the experiments (see Figure 1a), as previously described [97]. Infected mice were held in a reverse light/dark cycle so that parasites harvested at 08:00 h were at the late trophozoite stage. For studies in vitro, blood was collected when parasitemia was 30-40%. Infected blood was recovered into heparin (10 IU/ml) by cardiac puncture and diluted in phosphate-buffered saline (PBS Invitrogen, Paisley, UK) to the required concentration of pRBCs.

At various times following malaria infection, mice were immunized intravenously with 500 μg OVA (Sigma-Aldrich, Poole, UK), or a conjugate of OVA and HEL (Biozyme, Gwent, UK) [50], along with 50 ng LPS (from Salmonella equi-abortus Sigma-Aldrich).

Preparation of bone-marrow DCs

DCs were prepared from bone marrow as previously described [98]. Cell suspensions were obtained from femurs and tibias of female BALB/c mice. The bone-marrow cell concentration was adjusted to 5 × 10 5 cells/ml and cultured in six-well plates (Corning Costar, New York, USA) in complete RPMI (cRPMI: RPMI 1640 supplemented with L-glutamine (2 mM), penicillin (100 U/ml), streptomycin (100 μg/ml) (all from Invitrogen) and 10% fetal calf serum (FCS Labtech International, Ringmer, UK) containing 10% of culture supernatant from X63 myeloma cells transfected with mouse granulocyte-macrophage colony stimulating factor (GM-CSF) cDNA. Fresh medium was added to the cell cultures every 3 days. On day 6, DCs were harvested and cultured at the required concentration for each individual experimental procedure, as described below. This technique generated a large number of CD11c + DCs largely free from granulocyte and monocyte contamination, as previously described [98].

In vitroculture of DCs with fixed infected or uninfected erythrocytes

Blood from P. chabaudi AS-infected mice was washed twice in PBS before being resuspended in cRPMI for addition to DCs. For fixation, infected blood was washed three times in PBS and resuspended in 0.5% paraformaldehyde for 30 min at 4°C. Fixed erythrocytes were then washed in PBS, resuspended in 0.06% Gly-Gly (Sigma-Aldrich) for 5 min at 4°C and washed twice more in PBS before being resuspended in cRPMI for addition to DC. After 24 h culture, DCs were stimulated with 1 μg/ml LPS and the expression of cell-surface molecules was analyzed 18 h later by flow cytometry. To confirm complete fixation, we showed that 2 × 10 7 fixed, infected erythrocytes could not establish infection when injected intra-peritoneally into a female BALB/c mouse.

In vitroculture of CD40L-transfected fibroblasts with DCs

The cell lines 3T3-CD40L and 3T3-SAMEN [46] were kind gifts from P. Hwu (NCI, Bethesda, USA). Cells were grown in cRPMI in T75 tissue culture flasks (Helena Biosciences, Gateshead, UK) and, when confluent, harvested and distributed in six-well plates at 2.5 × 10 5 cells/ml of cRPMI. Bone-marrow-derived DCs were cultured with infected or uninfected erythrocytes at a ratio of 1:100. After 24 h, DCs were harvested, resuspended at 1 × 10 6 cells/ml and cultured in a 1:1 ratio with either 3T3-CD40L or 3T3-SAMEN cells for a further 24 h. The level of CD40 expression on DCs was analyzed by flow cytometry and culture supernatants collected for IL-12 cytokine analysis.

T-cell stimulation in vitro

Bone-marrow DCs were centrifuged at 450 × g, resuspended at 1 × 10 6 cells/ml and 500 μl aliquots were distributed into 24-well tissue culture plates (Corning Costar) with pRBCs or RBCs. After 24 h incubation at 37°C in 5% CO2, DCs were antigen-loaded for 6 h with 5 mg/ml OVA (Worthington Biochemical, Freehold, USA). OVA-specific T cells were isolated from the mesenteric and peripheral lymph nodes of DO11.10 transgenic mice [96] on the SCID background and cultured at a 1:1 ratio with DCs. T-cell proliferation was assessed after 48, 72, 96 and 120 h of culture and assessed by incorporation of [ 3 H]thymidine (0.5 μCi/well) for the last 24 h of culture. Cells were harvested using a Betaplate 96-well harvester (Wallac Oy, Turku, Finland) and [ 3 H]thymidine incorporation measured on a Betaplate liquid scintillation counter (Wallac).

Cytokine assay

For the detection of IL-12 (p40 and p70) and IL-10, OptEIA™ enzyme-linked immunosorbent assay (ELISA) kits (Becton Dickinson, Oxford, UK) were used according to the manufacturer's instructions. For T-cell cytokines, Mouse Th1/Th2 6-Plex kit (Biosource, Nivelles, Belgium) was used according to the manufacturer's instructions. For analysis of cytokine production ex vivo, single-cell suspensions of spleen cells were prepared by rubbing through Nitex mesh (Cadisch & Sons, London, UK) in RPMI 1640 medium. After washing, cells were resuspended at 4 × 10 6 cells/ml in cRPMI, either alone or with 1 mg/ml OVA or 5 μg/ml concanavalin A (ConA Sigma-Aldrich) and supernatants sampled after 48 h. These were stored at -20°C until analysis by standard sandwich ELISA protocol (antibodies used: for IFN-γ capture, R4-6A2 for IFN-γ detection, XMG1.2 for IL-5 capture, TRKF5 for IL-5 detection, TRKF4 Pharmingen, Oxford, UK) and the levels of cytokine in supernatants calculated by comparison with recombinant cytokine standards (R & D Systems, Abingdon, UK).

Flow cytometry

Aliquots of 1 × 10 6 cells in 12 × 75 mm polystyrene tubes (Falcon BD, Oxford, UK) were resuspended in 100 μl FACS buffer (PBS, 2% FCS and 0.05% NaN3) containing Fc Block (2.4G2 hybridoma supernatant) as well as the appropriate combinations of the following antibodies: anti-CD4-PerCP (clone RM4-5), anti-CD11c-PE (clone HL3), anti-CD40-FITC (clone 3/23), anti-CD69-PE (clone H1.2F3), anti-CD80-FITC (clone 16-10A1), anti-CD86-FITC (clone GL1), anti-MHC-II (clone 2G9), anti-B220-PE (clone RA3-6B2), PE-hamster IgG isotype control, FITC-rat IgG2a, κ isotype control and FITC-hamster IgG1, λ isotype control (anti-TNP) (all Pharmingen), biotinylated KJ1.26 antibody or biotinylated HEL. Biotinylated antibodies were detected by incubation with fluorochrome-conjugated streptavidin (Pharmingen). After washing, samples were analyzed using a FACSCalibur flow cytometer equipped with a 488 nm argon laser and a 635 nm red diode laser and analyzed using CellQuest software (both BD BioSciences, Oxford, UK).

Preparation of erythrocyte ghosts from infected and uninfected mouse blood

Ghosts from infected and uninfected erythrocytes were generated as previously described [67]. Briefly, blood was collected into heparin by cardiac puncture and washed three times in PBS. Infected and uninfected erythrocytes were concentrated in PBS supplemented with 113 mM glucose (Sigma-Aldrich) and 3% FCS. Infected erythrocytes were incubated in an equal volume of glycerol buffer (10% glycerol (Sigma-Aldrich) supplemented with 5% FCS in PBS) for 1 h at 4°C. Parasites and ghosts were separated in a continuous Percoll (Amersham Biosciences, Little Chalfont, UK) gradient (ρ: 1.02-1.10 g/cm 3 ) in intracellular medium buffer (IM: 20 mM NaCl, 120 mM KCl, 1 mM MgCl2, 10 mM glucose, 5 mM Hepes pH 6.7) by centrifugation at 5,000 × g for 30 min. Ghosts were then washed in IM buffer and layered on a two-step Percoll gradient (ρ: 1.01+1.02 g/cm 3 ) to separate them from ghosts that might still contain parasites. Ghosts from uninfected erythrocytes were obtained by adding a 40-fold volume of phosphate buffer (5 mM NaH2PO4/Na2HPO4, 1 mM PMSF, 0.01% azide, pH 8.5). The suspension was centrifuged at 32,000 × g for 30 min. Ghosts from infected and uninfected erythrocytes were then washed three times in PBS before being resuspended in cRPMI for addition to DCs at a ratio of 100:1.

Hemozoin preparation

HZ was isolated from supernatants obtained from cultures of P. falciparum gametocytes, kindly provided by Lisa Ranford-Cartwright, (Division of Infection and Immunity, University of Glasgow, UK). Endotoxin-free buffers and solutions were used throughout. Supernatants were centrifuged for 20 min at 450 × g. The pellet was washed three times in 2% SLS and resuspended in 6 M guanidine HCl. Following 5-7 washes in PBS, the pellet was resuspended in PBS and sonicated for 90 min using Soniprep 150 (Sanyo Scientific, Bensenville, USA) at an amplitude of 5-8 μm to minimize aggregation and maintain the HZ in suspension. Total heme content was determined as previously described [99] by depolymerizing heme polymer in 1 ml of 20 mM NaOH and 2% SDS, incubating the suspension at room temperature for 2 h and then reading the optical density at 400 nm using a UV-visible Helios spectrophotometer (Thermo Spectronic, Cambridge, UK). DCs were pulsed with 1-20 μM HZ - a concentration range similar to that seen when DCs were cultured at a 1:100 ratio with pRBCs.

Assessment of antigen-specific antibody responses

Peripheral blood was collected and the plasma was separated by centrifugation at 450 × g for 10 min and stored at -20°C until analysis. OVA-specific IgG was measured by standard sandwich ELISA using a peroxidase-conjugated anti-mouse total IgG (Sigma-Aldrich).

Adoptive transfer of antigen-specific lymphocytes

Lymph nodes and spleens were homogenized and the resulting cell suspensions washed twice by centrifugation at 400 × g for 5 min and resuspended in RPMI. The proportions of antigen-specific T cells were evaluated by flow cytometry, and syngeneic recipients received 3 × 10 6 antigen-specific cells. In some experiments, cells were labeled with the fluorescent dye CFSE (Molecular Probes, Oregon, USA) immediately before use [100]. The level of CFSE in cells was analyzed by flow cytometry and expressed as the mean proportion of antigen-specific T cells under each CFSE peak.


Spleens were frozen in liquid nitrogen in OCT embedding medium (Miles, Elkart, USA) in cryomoulds (Miles) and stored at -70°C. Tissue sections (8 μm) were cut on a cryostat (ThermoShandon, Cheshire, UK) and stored at -20°C. Sections were blocked and stained as previously described [55], using B220-FITC to stain B-cell areas and biotinylated-KJ1.26 to detect OVA-specific DO11.10 cells, and visualized using Streptavidin-Alexa Fluor 647 (Molecular Probes). All photographs were taken at 20× magnification.

To visualize HZ deposition in DCs, cells were photographed using an Axiovert S-100 Zeiss microscope using a 63× oil-immersion lens by normal bright-field imaging. To image HZ in splenic DC, 8 μm sections were cut as described above and stained with biotinylated-CD11c followed by Streptavidin-HRP and finally tyramide-488 (PerkinElmer, Boston, USA). Images were then taken of bright-field and green fluorescence and the images merged by inverting and then false coloring the bright-field image such that deposited HZ appeared red and CD11c appeared green.

Laser-scanning cytometry

Sections were stained as described above. Sections were then scanned on a laser-scanning cytometer equipped with argon, helium, neon, and ultraviolet lasers (Compucyte, Cambridge, USA) and visualized with the Openlab imaging system (Improvision, Coventry, UK). The localization of transgenic T cells and B-cell follicles were plotted. Using these tissue maps the number of transgenic T cells in defined gates was calculated for three gates in periarteriolar lymphoid sheath (PALS) and three B-cell follicle gates per section. Data are plotted as the mean proportion of transgenic T cells in each gate relative to the number of transgenic T cells in the entire section and are the mean of triplicate readings from three mice per group.

Isolation of DCs from spleen

Spleens were excised and single-cell suspensions obtained as described above. In some experiments, cells were stimulated with 1 μg/ml LPS for 18 h before analysis by flow cytometry. To obtain purified DCs from spleens of mice, single-cell suspensions were labeled using a CD11c isolation kit (Miltenyi Biotec, Bisley, UK) according to the manufacturer's instructions. DCs were then purified using two MS magnetic columns (Miltenyi Biotec) and found to be 85-95% pure by flow cytometric analysis.

Statistical analysis

Results are expressed as mean ± standard error or standard deviation as indicated. Significance was determined by one-way ANOVA in conjunction with the Tukey test using Minitab. A p-value of less than 0.05 was considered significant.

Toward synthetic detection platforms

Despite breakthroughs in our molecular understanding of NLR activation, knowledge of subsequent signaling steps and mechanisms remains weak. The pathways that connect NLR activation to outputs such as transcription of defense genes, changes in cell permeability, localized cell death, and systemic signaling remain poorly understood. Do activated, or dimerized, or oligomerized plant NLRs recruit new signaling proteins? How distinct are the signaling pathways controlled by the various N-terminal signaling domains recruited to the NLR chassis during evolution? Are integrated decoy domain NLRs modular? Can we engineer new or additional decoy domains into them to create or extend NLR function? As more structural and mechanistic information emerges on how plant and animal NLRs function, the engineering of novel, bespoke, and useful recognition capacities in plant and animal immune systems will become a more realistic goal.

Therapeutic options targeting immune deviation

Three major concepts emerge concerning therapeutic and preventive options in COVID-19: (1) targeting the virus and its cellular life cycle by antiviral drugs, (2) developing vaccines that can either prevent or mitigate disease symptoms after infection, and (3) targeting the deviation of the immune response to avoid or mitigate severe and fatal disease outcome ( Riva etਊl., 2020 Vabret etਊl., 2020 ). Targeting the innate immune system might play a role in all three areas.

The antivirals are divided in direct and indirect acting antivirals, targeting molecules and mechanisms of the virus itself or host cell proteins, respectively. Because SARS-CoV-2 antagonizes the type I IFN system, drugs strengthening this cellular defense system might improve early innate immune responses. Type I IFN therapy in patients with genetic deficits in the IFN system ( Zhang etਊl., 2020a ), but not in those with autoimmune phenocopies of these deficits ( Bastard etਊl., 2020 ), might be beneficial if provided sufficiently early ( Hadjadj etਊl., 2020 Wang etਊl., 2020b ). More than 20 clinical trials are currently evaluating the efficacy of type I IFN treatment (, accessed 2021/01/19) ( Wang etਊl., 2020b Zhou etਊl., 2020a ), the best time window, and benefits versus risks of IFN therapy. Alternatives such as IFNλ (type III IFN) only targeting receptors on epithelial cells without the broader effects of type I IFNs ( Prokunina-Olsson etਊl., 2020 ) are also under clinical evaluation. Other indirect antivirals blocking viral cell entry (e.g., by targeting proteases such as TMPRSS2) have been suggested as potential therapies ( Kaur etਊl., 2021 ), yet definitive proof for clinical efficacy is still lacking. Antiviral protein interaction mapping revealed further promising sets of antivirals: those that affect translation and those that modulate the sigma-1 and sigma-2 receptors, the cellular interaction partners of SARS-CoV-2 NSP6 and ORF9c ( Gordon etਊl., 2020 ).

Based on results from phase-III vaccine trials utilizing mRNA vaccines ( Anderson etਊl., 2020 Polack etਊl., 2020 ), two vaccines have been approved in the United States, United Kingdom, Israel, and the European Union, and several million individuals have been vaccinated since late 2020. A most surprising finding in light of age-related changes in the adaptive and the innate immune system is the similarly high efficiency of these vaccines in the elderly population. This unexpected success requires further mechanistic and molecular evaluations about the elicited immune response because this might give insights how age-related alterations of the immune system are overcome by this type of vaccination.

The third strategy is targeting the deviation of the immune response to avoid or mitigate severe and fatal disease outcomes. A starting point for many therapeutic strategies has been the hyperinflammatory state in severe disease ( Tang etਊl., 2020 Wang etਊl., 2020a ). Not surprisingly, trials targeting cytokines such as IL-6, IL-1, IFNγ, IL-1R, TNF, CXCL8, GM-CSF, GM-CSF receptor, or IL-37 have been reported, as well as strategies attempting to achieve disruption of chemokine signaling (e.g., via CCR1, CCR2, and CCR5) to prevent overt innate immune cell recruitment into the lung ( Wang etਊl., 2020a ). Because COVID-19 presents with such heterogeneity, a certain drug might be beneficial in one setting, while having no effect in another. For example, inconsistent results have been reported from large clinical trials when trying to inhibit IL-6 associated with hyperinflammation ( Huang and Jordan, 2020 ). A randomized clinical trial assessing tocilizumab, an anti-IL-6 antibody ( Stone etਊl., 2020 ), showed no benefit for moderately ill patients concerning effectiveness of preventing intubation or death. In contrast, among critically ill patients, the risk of in-hospital mortality was lower in patients treated with tocilizumab in the first 2ꃚys of ICU admission ( Gupta etਊl., 2021 ), which has also been reported in earlier trials ( Huang and Jordan, 2020 ). It cannot yet be ruled out that targeting IL-6 might be beneficial for a group of patients in specific clinical settings. This might be similarly true for targeting IL-1 with anakinra for which several smaller studies were reporting beneficial effects ( Iglesias-Julián etਊl., 2020 Kooistra etਊl., 2020 ), yet results from larger randomized trials are still missing.

Whether targeting single effector molecules will be efficient in disrupting the COVID-19-associated immune deviation awaits the report of ongoing clinical trials. Targeting several of these pathways simultaneously (e.g., by inhibiting Janus kinases) might overcome such limitations ( McCreary and Pogue, 2020 Wu and Yang, 2020 ). In early clinical trials, the use of the JAK inhibitor baricitinib showed a reduction in serum levels of IL-6, IL-1β, and TNF ( Bronte etਊl., 2020 ), suppressed the production of proinflammatory cytokines in lung macrophages, and the recruitment of neutrophils to the lung ( Hoang etਊl., 2021 ). Randomized clinical trials have to be initiated to validate these promising results. Along these lines, therapies targeting the kallikrein-kinin system with icatibant ( van de Veerdonk etਊl., 2020 ), or the coagulation system with antibodies against C5a and C3a ( Mastellos etਊl., 2020 ), have been introduced as additional options to ameliorate clinical symptoms and reduce mortality rates. Further, these therapeutic strategies might be considered in combination with immunotherapies such as anti-IL-6 or anti-IL-1 in severe COVID-19.

Reverse transcriptomics of blood immune cells derived from COVID-19 patients predicted the broadly anti-inflammatory drug dexamethasone and other corticosteroids as potentially beneficial for a subgroup of severely ill COVID-19 patients ( Aschenbrenner etਊl., 2021 ). Indeed, dexamethasone was shown to be beneficial, particularly in patients with severe disease courses where it reduced 28-day mortality in randomized clinical trials ( RECOVERY Collaborative Group etਊl., 2021 Tomazini etਊl., 2020 WHO Rapid Evidence Appraisal for COVID-19 Therapies (REACT) Working Group etਊl., 2020 ). Further, molecular prediction of drug responses may guide the way for precision medicine approaches following patient stratification.

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How the surfaces of silicone breast implants affect the immune system

Every year, about 400,000 people receive silicone breast implants in the United States. According to data from the U.S. Food and Drug Administration, a majority of those implants needs to be replaced within 10 years due to the buildup of scar tissue and other complications.

A team led by MIT researchers has now systematically analyzed how the varying surface architecture found in these implants influences the development of adverse effects, which in rare cases can include an unusual type of lymphoma.

"The surface topography of an implant can drastically affect how the immune response perceives it, and this has important ramifications for the [implants'] design," says Omid Veiseh, a former MIT postdoc. "We hope this paper provides a foundation for plastic surgeons to evaluate and better understand how implant choice can affect the patient experience."

The findings could also help scientists to design more biocompatible implants in the future, the researchers say.

"We are pleased that we were able to bring new materials science approaches to better understand issues of biocompatibility in the area of breast implants. We also hope the studies that we conducted will be broadly useful in understanding how to design safer and more effective implants of any type," says Robert Langer, the David H. Koch Institute Professor at MIT and the senior author of the study.

Veiseh, who is now an assistant professor at Rice University, and Joshua Doloff, a former MIT postdoc who is now an assistant professor at Johns Hopkins University, are the lead authors of the paper, which appears today in Nature Biomedical Engineering. The research team also includes scientists from Rice University, Johns Hopkins, Establishment Labs, and MD Anderson Cancer Center, among other institutions.

Surface analysis

Silicone breast implants have been in use since the 1960s, and the earliest versions had smooth surfaces. However, with these implants, patients often experienced a complication called capsular contracture, in which scar tissue forms around the implant and squeezes it, creating pain or discomfort as well as visible deformation of the implant. These implants could also flip after implantation, requiring them to be surgically adjusted or removed.

In the late 1980s, some companies began making implants with rougher surfaces, with the hopes of reducing capsular contracture rates and making them "stick" better to the tissue and stay in place. They did this by creating a surface with peaks extending up to hundreds of microns above the surface.

However, in 2019, the FDA requested a breast implant manufacturer to recall all highly textured breast implants (about 80 microns) marketed in the United States due to risk of breast implant-associated anaplastic large cell lymphoma, a cancer of the immune system.

A new generation of breast implants that dates back a decade, having a unique and patented surface architecture that includes not only a slight degree of surface roughness, with an average of about 4 microns, but also other specific surface characteristics including skewness and the number, distribution, and size of contact points optimized to cellular dimensions, was designed to prevent those complications.

In 2015, Doloff, Veiseh, and researchers from Establishment Labs teamed up to explore how this unique surface, as well as others commonly used, interact with the surrounding tissue and the immune system. They began by testing five commercially available implants with different topographies, including degree of roughness. These included the highly textured one that had been previously recalled, one that is completely smooth, and three that are somewhere in between. Two of these implants had the aforementioned novel surface architecture, one with a 4-micron roughness and one with a 15-micron roughness, manufactured by Establishment Labs.

In a study of rabbits, the researchers found that tissue exposed to the roughest implant surfaces showed signs of increased activity from macrophages -- immune cells that normally clear out foreign cells and debris.

All of the implants stimulated immune cells called T cells, but in different ways. Implants with rougher surfaces stimulated more pro-inflammatory T cell responses, while implants with the unique surface topography, including 4-micron average roughness, stimulated T cells that appear to inhibit tissue inflammation.

The researchers' findings suggest that rougher implants rub against the surrounding tissue and cause more irritation. This may offer an explanation for why the rougher implants can lead to lymphoma: The hypothesis is that some of the texture sloughs off and gets trapped in nearby tissue, where it provokes chronic inflammation that can eventually lead to cancer.

The researchers also tested miniaturized versions of these implants in mice. They manufactured these implants using the same techniques used to manufacture the human-sized versions, and showed that more highly textured implants provoked more macrophage activity, more scar tissue formation, and higher levels of inflammatory T cells. The researchers also performed single-cell RNA sequencing of immune cells from these tissues to confirm that the cells were expressing pro-inflammatory genes.

"While completely smooth surface implants also had higher levels of macrophage response and fibrosis, it was very clear in mice that individual cells were more stressed and were expressing more of a pro-inflammatory phenotype in response to the highest surface roughness," Doloff says.

On the other hand, implants with the unique surface architecture, including an optimized degree or "sweet spot" of surface roughness, at about 4 microns on average, and other specific characteristics, appeared to significantly reduce the amount of scarring and inflammation, compared to either the implants with higher roughness or a completely smooth surface.

"We believe that this is due to such surface architecture existing on the scale of individual cells of the body, allowing the cells to perceive them in a different way," Doloff says.

Toward safer implants

After performing their animal studies, the researchers analyzed samples from a large bank of cancer tissue samples at MD Anderson to study how human patients respond to different types of silicone breast implants.

In those samples, the researchers found evidence for the same types of immune responses that they had seen in the animal studies. Among their findings, they observed that tissue samples that had been host to highly textured implants for many years showed signs of a chronic, long-term immune response. They also found that scar tissue was thicker in patients who had more highly textured implants.

"Doing across-the-board comparisons in mice, rabbits, and then in human [tissue samples] really provides a much more robust and substantial body of evidence about how these compare to one another," Veiseh says.

The authors hope that their datasets will help other researchers optimize the design of silicone breast implants and other types of medical silicone implants for better safety.

"The importance of science-based design that can provide patients with safer breast implants was confirmed in this study," says Roberto de Mezerville, an author of the paper and head of R&D at Establishment Labs. "By demonstrating for the first time that an optimal surface architecture allows for the least possible inflammation and foreign-body response, this work is a significant contribution to the entire medical device industry."

Watch the video: The Immune System: Innate Defenses and Adaptive Defenses (November 2022).