Over the last few decades, it has been shown that there is a huge reproducibility crisis going on in the sciences. This was brilliantly pointed out by John Ioannidis, a very well-respected physician/scientist and professor at Stanford, who concluded in a 2005 essay he wrote that most of the published scientific literature is wrong. One of the reasons for this comes down to a lack of reproducibility and replication:
“Several methodologists have pointed out [9–11] that the high rate of nonreplication (lack of confirmation) of research discoveries is a consequence of the convenient, yet ill-founded strategy of claiming conclusive research findings solely on the basis of a single study.“
Over the years, it has been shown that the lack of reproducibility has been discovered in many areas related to virology including cell cultures, genomics, and PCR. So knowing that most of the scientific literature is wrong and extends to many of the areas virology incorporates, it shouldn’t come as any surprise that this reproducibility crisis is happening in the world of antibodies as well.
Below are highlights from 4 articles detailing the antibody reproducibility crisis. The evidence was first presented in 2015 and I’ve included articles from the last few years to show there hasn’t been any improvement since.
This first source is a Nature article from May 2015. It squarely lays the gauntlet down at the feet of antibody research for the lack of reproducibility and replicability in biological science. The author provides many examples from different researchers for how the lack of specificity, considered a staple of antibodies, creates irreproducible results and false findings. The article discusses the missing standardization and quality controls in antibody research and details the role manufacturers have on the variability of the antibodies sold and used which leads to wasted time and resources due to many failed experiments:
Reproducibility crisis: Blame it on the antibodies
“Antibodies are the workhorses of biological experiments, but they are littering the field with false findings. A few evangelists are pushing for change.
In 2006, things were looking pretty good for David Rimm, a pathologist at Yale University in New Haven, Connecticut. He had developed a test to guide effective treatment of the skin cancer melanoma, and it promised to save lives. It relied on antibodies — large, Y-shaped proteins that bind to specified biomolecules and can be used to flag their presence in a sample. Rimm had found a combination of antibodies that, when used to ‘stain’ tumour biopsies, produced a pattern that indicated whether the patient would need to take certain harsh drugs to prevent a relapse after surgery. He had secured more than US$2 million in funding to move the test towards the clinic.
But in 2009, everything started to fall apart. When Rimm ordered a fresh set of antibodies, his team could not reproduce the original results. The antibodies were sold by the same companies as the original batches, and were supposed to be identical — but they did not yield the same staining patterns, even on the same tumours. Rimm was forced to give up his work on the melanoma antibody set. “We learned our lesson: we shouldn’t have been dependent on them,” he says. “That was a very sad lab meeting.”
Antibodies are among the most commonly used tools in the biological sciences — put to work in many experiments to identify and isolate other molecules. But it is now clear that they are among the most common causes of problems, too. The batch-to-batch variability that Rimm experienced can produce dramatically differing results. Even more problematic is that antibodies often recognize extra proteins in addition to the ones they are sold to detect. This can cause projects to be abandoned, and waste time, money and samples.
Many think that antibodies are a major driver of what has been deemed a ‘reproducibility crisis’, a growing realization that the results of many biomedical experiments cannot be reproduced and that the conclusions based on them may be unfounded. Poorly characterized antibodies probably contribute more to the problem than any other laboratory tool, says Glenn Begley, chief scientific officer at TetraLogic Pharmaceuticals in Malvern, Pennsylvania, and author of a controversial analysis1 showing that results in 47 of 53 landmark cancer research papers could not be reproduced.
A few scientists who have been burned by bad experiences with antibodies have begun to speak up. Rimm’s disappointment set him on a crusade to educate others by writing reviews, hosting web seminars and raising the problem in countless conference talks. He and others are calling for the creation of standards by which antibodies should be made, used and described. And some half a dozen grass-roots efforts have sprung up to provide better ways of assessing antibody quality.”
Take the example of Ioannis Prassas, a proteomics researcher at Mount Sinai Hospital in Toronto, Canada. He and his colleagues had been chasing a protein called CUZD1, which they thought could be used to test whether someone has pancreatic cancer. They bought a protein-detection kit and wasted two years, $500,000 and thousands of patient samples before they realized that the antibody in the kit was recognizing a different cancer protein, CA125, and did not bind to CUZD1 at all2. In retrospect, Prassas says, a rush to get going on a promising hypothesis meant that he and his group had failed to do all the right tests. “If someone says, ‘Here is an assay you can use,’ you are so eager to test it you can forget that what has been promised is not the case.”
Most scientists who purchase antibodies believe the label printed on the vial, says Rimm. “As a pathologist, I wasn’t trained that you had to validate antibodies; I was just trained that you ordered them.”
“Since the 1970s, scientists have exploited antibodies for research. If a researcher injects a protein of interest into a rabbit, white blood cells known as B cells will start producing antibodies against the protein, which can be collected from the animal’s blood. For a more consistent product, the B cells can be retrieved, fused with an ‘immortalized’ cell and cultured to provide a theoretically unlimited supply.
Three decades ago, scientists who needed antibodies for their experiments had to make them themselves. But by the late 1990s, reagent companies had started to take over the chore.
Today, more than 300 companies sell over 2 million antibodies for research. As of 2011, the market was worth $1.6 billion, according to global consultancy Frost & Sullivan.
There are signs that problems with antibodies are having broad and potentially devastating effects on the research record. In 2009, one journal devoted an entire issue to assessing the antibodies that are used to study G-protein-coupled receptors (GPCRs) — cell-signalling proteins that are targeted by drugs to treat various disorders, from incontinence to schizophrenia. In an analysis3 of 49 commercially available antibodies that targeted 19 signalling receptors, most bound to more than one protein, meaning that they could not be trusted to distinguish between the receptors.
The field of epigenetics relies heavily on antibodies to identify how proteins that regulate gene expression have been modified. In 2011, an evaluation4 of 246 antibodies used in epigenetic studies found that one-quarter failed tests for specificity, meaning that they often bound to more than one target. Four antibodies were perfectly specific — but to the wrong target.
Scientists often know, anecdotally, that some antibodies in their field are problematic, but it has been difficult to gauge the size of the problem across biology as a whole. Perhaps the largest assessment comes from work published by the Human Protein Atlas, a Swedish consortium that aims to generate antibodies for every protein in the human genome. It has looked at some 20,000 commercial antibodies so far and found that less than 50% can be used effectively to look at protein distribution in preserved slices of tissue5. This has led some scientists to claim that up to half of all commercially available antibodies are unreliable.
But reliability can depend on the experiment. “Our experience with commercial antibodies is that they are usually okay in some applications, but they might be terrible in others,” says Mathias Uhlén at the Royal Institute of Technology in Stockholm, who coordinates the Human Protein Atlas.
Researchers ideally should check that an antibody has been tested for use in particular applications and tissue types, but the quality of information supplied by vendors can vary tremendously. A common complaint from scientists is that companies do not provide the data required to evaluate a given antibody’s specificity or its lot-to-lot variability. Companies might ship a batch of antibodies with characterization information derived from a previous batch. And the data are often derived under ideal conditions that do not reflect typical experiments. Antibody companies contacted for this article said that it is impossible to test their products across all experimental conditions, but they do provide reliable data and work with scientists to improve antibody quality and performance.
Many academics use Google to find products, so optimizing search results can sometimes matter more to a company than optimizing the actual reagents, says Tim Bernard, head of the biotechnology consultancy Pivotal Scientific in Upper Heyford, UK. Christi Bird, a Frost & Sullivan analyst based in Washington DC, says that researchers are often more interested in how quickly reagents can be delivered than in searching for antibodies with appropriate validation data. “It’s the Amazon effect: they want it in two or three days, with free shipping.”
Researchers who are aware of the antibody problem say that scientists need to be more vigilant. “Antibodies are not magic reagents. You can’t just throw them on your sample and expect the result you get is 100% reliable without putting some critical thinking into it,” says James Trimmer, head of NeuroMab at the University of California, Davis, which makes antibodies for neuroscience. Like many suppliers, NeuroMab explicitly states the types of experiment that an antibody should be used for, but scientists do not always follow the instructions.”
“By necessity, many researchers rely on word of mouth or the published literature for advice. But that creates a self-perpetuating problem, in which better-performing antibodies that become available later are rarely used, says Fridtjof Lund-Johansen, a proteomics researcher at the University of Oslo. “We have very good antibodies on the market,” he says, “but we don’t know what they are.” Lund-Johansen is trying to change that by developing high-throughput assays that could compare thousands of antibodies at once.”
“Some scientists are calling for much more radical change. In a Comment in Nature in February7, Andrew Bradbury of Los Alamos National Laboratory in New Mexico and more than 100 co-signatories proposed a massive shift in the way antibodies are produced and sold. They suggested using only antibodies that have been defined down to the level of the DNA sequence that produces them, and then manufactured in engineered ‘recombinant’ cells. This would circumvent much of the variability introduced by production in animals. But the proposal demands information about individual antibodies that many companies consider to be trade secrets — and the antibody marketplace and its millions of products would have to be essentially demolished and reconstructed.“
“The pressure to characterize currently available antibodies is surging. As part of efforts to improve reproducibility, some researchers have started to discuss enlisting an independent body to establish a certification programme for commercial antibodies. And several journals (including Nature) ask authors to make clear that antibodies used in their papers have been profiled for that particular application.
The quality will creep, rather than leap, forward, says Trimmer, who hopes to see a positive-feedback loop: as scientists become aware of artefacts, they will be more likely to challenge results and uncover more artefacts. Already, he says, the widespread insouciance about antibody validation has started to fade. “It’s turning around a little bit,” he says. “We need to keep talking about it.”
This next article is from September 2019 and it tackles the question of who is responsible for the antibody reproducibility crisis and addresses the impact manufacturers have due to inconsistent lots and batch-to-batch variability. It discusses the importance of proper characterization and validation of antibodies and antigens:
Antibody Validation… Is There Still A Crisis?
“Reliable antibodies are essential: whether you are planning to publish a ground-breaking piece of research, or are carrying out routine assays within your laboratory; reproducibility is key.
Over the years there has been much debate regarding who should take responsibility for antibody validation. Is it the responsibility of the antibody supplier to offer a fully characterised and validated antibody, or should the researcher validate the antibody specifically for their own needs? Initially there was a greater onus on the researcher to check an antibody performed as it should in their assays. Current opinion places a larger obligation on the antibody manufacturer to ensure lot to lot consistency and specificity for the antibody target. As part of our State of the Industry survey published in our 2019 antibody market report, the manufacturers themselves were polled for their opinions on antibody validation. A larger percentage of manufacturers, compared to the previous year, believed antibody validation is a problem that should be tackled by the industry. Only 45.8% of the companies polled in the 2018 survey thought it was an industry problem compared to 57.6% in 2019. When asked to give suggestions on how to improve quality standards, 37% suggested the implementation of global standards.”
“A bigger shake up of the research reagent market was presented in the publication by Bradbury and Pluckthun in the scientific journal Nature. Bradbury, Pluckthun and 110 co-signatories called for funding to allow the genetic sequencing of all hybridoma-produced monoclonal antibodies to key targets. Describing inconsistent levels of characterisation between manufacturers, and potential problems associated with hybridomas. They proposed that replacing these antibodies with recombinant versions would ensure a never-ending supply of highly-characterised antibodies. Thus, promoting the transition towards the exclusive use of recombinant antibodies, and even suggesting the phasing out of polyclonal antibodies altogether!”
At the 3rd International Antibody Validation Meeting held in Bath, the importance of antigens in antibody generation, characterisation and validation was also stressed. Speakers highlighted the need for them to be full-length, correctly-folded, ‘authentic’ proteins for effective antibody generation. Furthermore, discussions included factors such as antigen abundance and availability, which should be taken into account when planning an antibody characterisation and validation strategy. The role of the scientists purchasing these antibodies was not ignored, with an emphasis on correct usage, as antibody performance is application dependant.”
This second Nature article featured here is from September 2020. It highlights the issues related to the non-specificity of antibodies binding to proteins other than those intended. It provides examples of how this antibody non-specificity has been a consistent finding among researchers which has led to irreproducible and false results. It discusses the identity crisis in antibody research as it is unclear which antibodies are used in many published papers and calls on the scientific community to be skeptical of any antibody research results:
When antibodies mislead: the quest for validation
“Commercial antibodies are commonplace in biology laboratories. Researchers use these giant Y-shaped proteins to detect specific molecules in cells, tissues and test tubes. But sometimes the proteins detect other molecules, too — or even instead. When that happens, confusion can snowball.”
“Peter McPherson, a neuroscientist at McGill University in Montreal, Canada, suspects that the multiple locations arise from what is often seen as a trivial decision for detecting the protein: the choice of antibody. Antibodies work by binding to specific parts of a protein, according to the protein’s shape and chemical properties, but an antibody produced to bind to one protein can often bind to another, and sometimes with better affinity.
That’s borne out in McPherson’s work. He and his team bought 16 antibodies marketed to detect CR9ORF72. Then they took a cell line that produces the protein at high levels and used the genome-editing tool CRISPR–Cas9 to make a line in which CR9ORF72 was knocked out, so the protein would not be present. They then assessed how the antibodies performed in the two lines in a series of common tests and found that the antibody that had been used in the most publications (and cited most often) found the protein even when it wasn’t there. Those that worked best for each assay had not appeared in the literature at all1.
Others have reported comparable experiences. Cecilia Williams, a cancer researcher at the KTH Royal Institute of Technology in Stockholm, tested 13 antibodies to try to untangle conflicting data about estrogen receptor β, a protein discovered in 1996 that is a potential anticancer target. Twelve of the antibodies, including the two most popular, gave either false positives or false negatives, or both, she and her team reported2. “Don’t take either the literature or the antibody for granted,” she warns.
Researchers often buy antibodies according to the number of times the product has been cited in the literature, but that strategy can overlook newer products that have been put through more rigorous tests. They also tend to assume that others who used the antibody before them checked that it worked as intended, and that it will therefore work in their own experiments, opening the door for self-perpetuating artefacts.
“When I look at papers in general, I get depressed by the quality of the antibody characterization,” says Simon Goodman, a science consultant at the Antibody Society, a not-for-profit professional association. Goodman is based in Darmstadt, Germany, and has organized a series of educational webinars on appropriate techniques for the society3. “If you ask ‘how did you validate the antibody?’, researchers will say, ‘well we bought it and the producer says that it behaves like this.’”
Often, the data that companies provide to show an antibody works come from a cell line that has been engineered to express the protein at levels substantially higher than under physiological conditions.”
“Not every antibody can be tested using knockout controls, Edwards admits. About 10% of genes are essential to life, so a knockout cell line is not viable for them. Also, an antibody that performs well in one cell line could fall short in another.”
“That said, it takes more than just the right antibody to yield informative experiments, says James Trimmer, who directs the NeuroMab lab at the University of California, Davis, an effort to produce high-quality antibodies for neuroscience. An antibody that works reliably when a protein is in its folded (‘native’) state inside a cell can perform differently when proteins are chemically altered in preserved tissue or unfolded in cell mixtures, and even small changes in sample preparation can have a large impact.“
“Sometimes it’s not even clear which antibody researchers have used, especially in older studies. Only about 11% of the antibodies used in papers published in 1997 are identifiable, according to an analysis5 led by researchers at the University of California, San Diego (UCSD), and the data-sharing platform SciCrunch in La Jolla, California; nowadays, that figure has risen to 43%.”
“The bottom line is: however an antibody-driven experiment comes out, researchers would be wise to be sceptical. When experiments fail, researchers often question their own technique, says Goodman. “Of course you blame yourself as a young scientist.” But the scientific community should be equally sceptical of antibodies that seem to work, says Edwards, and demand evidence that they do before relying on them. “We buy antibodies, we don’t test them, and then we publish articles that send the field sideways.”
Sadly, this last article from March 2021 is no longer available. I originally highlighted it in May 2021 and I tried my usual tricks to find it but my efforts were unfortunately fruitless. The article provides the three primary reasons for this antibody reproducibility crisis: batch-to-batch variability, fragile and unstable hybridomas, and a lack of standardized validation. It is pointed out that an alarming number of scientists are coming forward with claims of irreproducibility in their antibody experiments and it discusses the unregulated state of the industry:
Antibody inaccuracy, non-specificity and irreproducibility at the root of research extinction
“Antibodies are integral to life sciences research and therapeutic and diagnostics discovery and development. However, they are inherently prone to variability. Even when expressed as monoclonal antibodies, cell culture systems may harbor mistakes that produce a different antibody, leading to batch-to-batch variability, and experimental irreproducibility. The term reproducibility crisis is a term coined in the early 2010s to denote the lack of consistency observed in research results, particularly as it pertained to immunoreagents. To solve this crisis, researchers have proposed robust protocols, and number identifiers to catalogue and track antibodies through publications to ensure reproducibility. However, these identifiers do not include the protein sequence as an important property that requires certification. In this review, we discuss why this paucity in protein sequence verification substantially contributes to antibody irreproducibility.“
“One of the most commonly used and critical reagents found in most biomedical research laboratories is central to what is known as “The Reproducibility Crisis”. An alarming number of researchers in the life sciences have noted irreproducibility in their antibody-based experiments, fueled by insights originally unearthed by A. Bradbury and C. Glenn Begley (1–3). Through their desire to highlight the unregulated state of the antibody industry, Bradbury and Begley have helped push the need for industry reform including the need for more rigorous testing and validation.
At the root of antibody irreproducibility is the challenge of batch variability. This occurs when antibodies are sold under the same catalogue number and by the same vendor, however exhibit different specificity and/or affinity. This is often the result of cell-culturing environments and/or different producing animals. Researchers not only need to overcome the challenges associated with commercial antibody production, if they opt to produce their own, they can face a multitude of other obstacles. Notably, maintaining the high-standard procedural controls to maintain cell line viability.
The challenges associated with antibody production and supply pose a significant problem for researchers, with the worst-case scenarios preventing experimental reproducibility.“
1. BATCH-TO-BATCH VARIABILITY – A SIDE EFFECT OF POLYCLONAL ANTIBODY DEVELOPMENT
“There are different factors contributing to the antibody reproducibility crisis. The first comes from the nature of antibody production. In human and animal bodies, antibodies are secreted by B cells in a polyclonal mixture of heterogeneous molecules that recognize and bind to different epitopes of an antigen. In the lab, polyclonal antibodies (pAbs) are produced by injecting a particular antigen into an animal that elicits an immune response. The pAbs secreted are then harvested from the animal and used in different antigen-specific experiments.
The reproducibility crisis of polyclonal-based development stems from batch-to-batch variability that commonly occurs during production. The problem arises when different host animals are injected with the same antigen but then produce pAbs that have different specificities and affinities. This means that even if one was to use a new batch of antibodies, they cannot reproduce the exact same experimental results. Even more importantly, the same animal sometimes may have different immune responses to the same antigen and also exhibit time-dependent variation known as the affinity maturation process.
2. FRAGILE, UNSTABLE HYBRIDOMAS ARE ENDANGERING MONOCLONAL ANTIBODIES
Ever since the breakthrough discovery of hybridoma technology by Köhler and Milstein in 1975, it has remained to be the primary method for scientists to produce monoclonal antibodies (mAbs). The process starts by injecting animals with specific antigen that provokes an immune response. Individual B cells producing antibodies that bind to the injected antigen are then isolated from the animal and fused with myeloma cells to produce a hybrid cell line called a hybridoma. By fusing short-lived antibody-producing B cells with immortal myeloma cells, hybridoma cells are expected to provide a never-ending supply of identical mAbs.
However, in the laboratory, hybridomas are often considered unstable and fragile, so they require high-standard procedural controls to maintain cell line viability. Although researchers spend a significant amount of time and effort on culturing hybridoma cell lines, poor growth or even cell death still occurs regularly. Under normal conditions, antibody contents can decrease continuously during the course of hybridoma cultivation (4). Many other factors can lead to failure of hybridoma survival. Long-time storage, repeated freeze-thaw cycles, improper handling, and contamination can all cause hybridoma death and permanent loss of important antibodies.
In addition, hybridoma cell lines are also known to undergo gene mutations and rearrangements over time, leading to antibody heterogeneity and batch-to-batch variability (5). A recent study of 185 clonal hybridoma cell lines identified nearly a third contained additional heavy or light chain genes, resulting in impaired affinity and specificity to the target antigen. An investigation conducted by Rapid Novor in 2019 showed similar results – among 80 research-purpose mAbs analyzed, a significant portion (14%) were shown to have a second light chain present (Figure 1). In other cases, hybridomas may even lose the chromosome containing antibody genes completely arresting the production of antibodies (6).
3. LACK OF STANDARDIZED VALIDATION – WHEN ANTIBODIES MISLEAD
Despite the complexity and uncertainty of antibody production, there is no standardized protocol or regulation for the validation of antibodies, including assessing their specificity, affinity, sequences, and applications in different assays.
Among over 2 million commercial antibodies provided by more than 300 vendors, the majority of them are polyclonal. The QC data listed on the product sheets are often obtained from previous batches and no longer valid for the ones delivered to users. With regard to mAbs, there is also no way of knowing if the current hybridoma cell line is characterized as stable and functional. This largely stems from the issue of inconsistent catalog numbers that have not accounted for new culturing environments, production animals or company merges. Lack of a proper validation leads to the release of a large number of poorly characterized antibodies (“bad antibodies”) to users for research. It was estimated that despite there being 2 million antibodies on the market, only 12.5 – 25% are considered unique ‘core’ antibodies (7).
When it comes to selecting key antibodies, the process varies by user and laboratory. For example, some labs regularly purchase from their trusted vendors, some rely on word of mouth, and some buy a few from different vendors and then test which one works. One similarity tends to exist, many researchers will reference publications in which their antibodies were referenced or will refer to the information provided on the product sheets. However, this still does not guarantee a perfectly safe decision. Take for example the following antibodies that were used to identify therapeutically relevant clinical biomarkers. Despite all of these antibodies being regularly cited in industry publications and journals for their respective use cases, all were shown to exhibit cross-reactivity resulting in significant sums of research resources being lost.
Thus, using antibodies as biomarker tools for detection can be potentially fatal if they have not been fully verified with rigorous scrutiny. The unfortunate reality is, it’s no longer sufficient to rely solely on vendor’s quality assurance protocols or scientific publications, it is necessary to independently assess and verify candidates.“
- Antibodies are the workhorses of biological experiments, but they are littering the field with false findings
- Numerous scientists have come forward claiming the inability to reproduce their own results using the same exact antibodies
- Batch-to-batch variability has led to consistently producing differing results and to proteins being bound that shouldn’t be
- Scientists burned by bad antibody results are calling for the creation of standards by which antibodies should be made, used and described
- Many believe antibodies are a main driver in the reproducibility crisis
- In an analysis of 49 commercially available antibodies that targeted 19 signalling receptors, most bound to more than one protein, meaning that they could not be trusted to distinguish between the receptors
- In 2011, an evaluation of 246 antibodies used in epigenetic studies found that one-quarter failed tests for specificity, meaning that they often bound to more than one target, and four antibodies were perfectly specific — but to the wrong target
- The Human Protein Atlas has looked at 20,000 commercial antibodies so far and found that less than 50% can be used effectively to look at protein distribution in preserved slices of tissue
- This has led some scientists to claim that up to half of all commercially available antibodies are unreliable
- Antibody reliability is dependent on the experiment – they are “usually OK” in some instances and terrible in others
- The lack of characterization of the antibodies has led to many false/unreproducible results
- The lack of specificity has been discovered with antibodies binding to more than one protein or not binding to the one they are supposed to
- Antibody vendors information varies tremendously as:
- They do not provide the data required to evaluate a given antibody’s specificity or its lot-to-lot variability
- They might ship a batch of antibodies with characterization information derived from a previous batch
- Their data is often derived under ideal conditions that do not reflect typical experiments
- They claim it is impossible to test their products across all experimental conditions
- Vendors are not supplying validated data on their antibody products
- Companies are more concerned with optimizing search results than optimizing the actual reagents
- Vendors are also more concerned with protecting trade secrets than supplying validation
- The pressure to characterize currently available antibodies is surging as:
- In an effort to improve reproducibility, some researchers have started to discuss enlisting an independent body to establish a certification programme for commercial antibodies
- Several journals (including Nature) are asking authors to make clear that antibodies used in their papers have been profiled for that particular application
- Current opinion is that the manufacturers should be in charge of addressimg the problems of lot-to-lot variability, specificity, and characterization
- A survey of antibody manufacturers found that, when asked to give suggestions on how to improve quality standards, 37% suggested the implementation of global standards
- An article by. Bradbury, Pluckthun, and 110 co-singees in the scientific journal Nature described inconsistent levels of characterisation between manufacturers, and potential problems associated with hybridomas
- Quick sidenote on Hybridomas:
- They are a hybrid cell used as the basis for the production of antibodies in large amounts for diagnostic or therapeutic use. Hybridomas are produced by injecting a specific antigen into a mouse, collecting an antibody-producing cell from the mouse’s spleen, and fusing it with a tumor cell called a myeloma cell. The hybridoma cells multiply indefinitely in the laboratory and can be used to produce a specific antibody indefinitely. (https://www.rxlist.com/hybridoma/definition.htm)
- There is an increasing effort to move away from polyclonal and monoclonal antibodies in favor of recombinant antibodies in order to solve the crisis
- Another quick side note: Recombinant Antibodies are mostly synthetic:
- “Basically, recombinant antibodies are monoclonal antibodies generated in vitro using synthetic genes. The technology involves recovering antibody genes from source cells, amplifying and cloning the genes into an appropriate phage vector, introducing the vector into a host (bacteria, yeast, or mammalian cell lines), and achieving expression of adequate amounts of functional antibody.” (https://www.google.com/amp/s/info.gbiosciences.com/blog/recombinant-antibodies-an-overview%3fhs_amp=true)
- At the 3td International Antibody Validation Meeting held in Bath, the importance of antigens in antibody generation, characterisation and validation was also stressed
- Speakers highlighted the need for them to be full-length, correctly-folded, ‘authentic’ proteins for effective antibody generation
- There was an emphasis on correct usage, as antibody performance is application dependant
- Antibodies produced to bind to one protein can often bind to another and sometimes with better affinity
- Cecilia Williams, a cancer researcher at the KTH Royal Institute of Technology in Stockholm, tested 13 antibodies and twelve of the antibodies, including the two most popular, gave either false positives or false negatives, or BOTH
- Researchers often use antibodies cited by other researchers and ASSUME they are checked/validated which leads to self-perpetuating artefacts
- The data that companies provide to show an antibody works come from a cell line that has been engineered to express the protein at levels substantially higher than under physiological conditions
- An antibody that performs well in one cell line could fall short in another
- An antibody that works reliably when a protein is in its folded (‘native’) state inside a cell can perform differently when proteins are chemically altered in preserved tissue or unfolded in cell mixtures, and even small changes in sample preparation can have a large impact
- Sometimes it’s not even clear which antibody researchers have used, especially in older studies
- Only about 11% of the antibodies used in papers published in 1997 are identifiable, according to an analysis led by researchers at the University of California, San Diego (UCSD),
- Many are warning that researchers should be skeptical of antibody research and any which show that antibodies work
- Antibodies are inherently prone to variability
- Even when expressed as monoclonal antibodies, cell culture systems may harbor mistakes that produce a different antibody, leading to batch-to-batch variability, and experimental irreproducibility
- The paucity (scarcity) in protein sequence verification substantially contributes to antibody irreproducibility
- An alarming number of researchers in the life sciences have noted irreproducibility in their antibody-based experiments
- The antibody industry is in an unregulated state
- At the root of antibody irreproducibility is the challenge of batch variability
- This refers to antibodies sold under the same catalogue number and by the same vendor yet they exhibit different specificity and/or affinity
- This is often the result of cell-culturing environments and/or different producing animals
- Lack of antibody specificity/affinity is due to the cell culturing environment
- The 3 main problems contributing to the reproducibility crisis:
- Batch-to-batch variability
- The reproducibility crisis of polyclonal-based development stems from batch-to-batch variability that commonly occurs during production
- The problem arises when different host animals are injected with the same antigen but then produce pAbs that have different specificities and affinities
- This means that even if one was to use a new batch of antibodies, they cannot reproduce the exact same experimental results
- Fragile, unstable hybridomas
- Hybridomas are often considered unstable and fragile, so they require high-standard procedural controls to maintain cell line viability
- Poor growth or even cell death still occurs regularly
- Long-time storage, repeated freeze-thaw cycles, improper handling, and contamination can all cause hybridoma death and permanent loss of important antibodies
- Hybridoma cell lines are also known to undergo gene mutations and rearrangements over time, leading to antibody heterogeneity and batch-to-batch variability
- A recent study of 185 clonal hybridoma cell lines identified nearly a third contained additional heavy or light chain genes, resulting in impaired affinity and specificity to the target antigen
- Hybridomas may even lose the chromosome containing antibody genes completely arresting the production of antibodies
- Lack of standardized validation
- There is no standardized protocol or regulation for the validation of antibodies, including assessing their specificity, affinity, sequences, and applications in different assays
- The QC data listed on the product sheets are often obtained from previous batches and no longer valid for the ones delivered to users
- With regard to monoclonal antibodies, there is also no way of knowing if the current hybridoma cell line is characterized as stable and functional
- Lack of a proper validation leads to the release of a large number of poorly characterized antibodies (“bad antibodies”) to users for research
- Antibodies that were used to identify therapeutically relevant clinical biomarkers and were regularly cited in industry publications and journals for their respective use cases, were all shown to exhibit cross-reactivity resulting in significant sums of research resources being lost
- It’s no longer sufficient to rely solely on vendor’s quality assurance protocols or scientific publications
- Batch-to-batch variability
It should be clear now, with the lack of proof of purified/isolated antibodies over the last century as well as the alarming reproducibility crisis, why researchers/scientists/Dr.’s etc. have no clue how to answer questions about antibodies. They can’t say how many antibodies are needed for protection. They can’t say if they offer lifetime immunity or any immunity at all. They can’t explain how antibodies can be a sign of protection in regards to vaccines yet are a sign of illness in regards to HIV. They can’t interpret the test results accurately, explain what they mean, nor provide any reasons for the high rates of false-positives. They simply don’t know anything about these hypothetical/theoretical particles because the “science” behind them is questionable at best and completely unreproducible/irreplicable.