Anthropic Life Sciences Team and Claude Uncover Novel CRISPR-Like Enzyme System

Anthropic Life Sciences Team and Claude Uncover Novel CRISPR-Like Enzyme System Anthropic's newly introduced life sciences research group announced early results where Claude autonomously identified a novel enzyme system in bacteriophages, designated array-associated reverse transcriptases (ART), which features repetitive DNA arrays reminiscent of CRISPR. Anthropic launched a life sciences lab in the Bay Area conducting BSL-1 and BSL-2 molecular biology research driven by Claude-generated hypotheses. A coordinated search involving roughly 950 Claude agents evaluated over 200,000 reverse transcriptases across 210 million tokens, discovering an uncharacterized enzyme system dubbed ART. The ART system consists of a reverse transcriptase, an adjacent accessory partner gene, and an array of evenly spaced DNA repeats that express short RNAs. Feng Zhang noted the finding of RNA-repeat arrays linked to reverse transcriptases as an intriguing example of AI-supported biological discovery. Discovery of Array-Associated Reverse Transcriptases Tasked via an initial prompt to explore a massive DNA sequence database for new reverse transcriptases, approximately 950 Claude agents processed data across 21 hours. The AI narrowed more than 200,000 enzymes down to 3,500 candidates and eventually 20 highly compelling systems, highlighting an RT in bacteriophages bordered by tandem repeat arrays. Anthropic's researchers designated this system array-associated reverse transcriptases (ART). Structure and Characteristics of ART The identified ART system consists of three main elements: the reverse transcriptase, a neighboring partner gene of unknown function, and a long array of evenly spaced non-coding DNA repeats. Initial experimental testing confirmed that the repeat array is expressed as a set of distinct short RNAs, paralleling the architecture that grants CRISPR systems their programmable targeting capabilities. Anthropic's Life Sciences Lab and AI Workflow Anthropic operates a Bay Area laboratory focusing on BSL-1 and BSL-2 research, where human scientists experimentally test and validate protein candidates generated by Claude. The workflow employs Claude Science, Claude Code, and multi-agent coordination to survey protein families, assess literature, and draft structured reports proposing biological functions, using feedback to align Claude's selection criteria with human scientific judgment.

Anthropic团队借助Claude自主发现类CRISPR新型酶系统ART Anthropic宣布成立生命科学研究组与实验室，并在科学家仅提供高级指令的情况下，利用Claude自主从海量DNA序列中发现了一种具有类似CRISPR重复阵列的新型噬菌体酶系统ART。 Anthropic设立新生命科学实验室，重点利用Claude进行基础生物学数据挖掘与实验验证，实验操作遵循BSL-1和BSL-2标准。 约950个Claude智能体耗时21小时、使用2.1亿Token，在庞大DNA数据库中筛选出新型阵列相关逆转录酶系统（ART）。 该ART系统包含逆转录酶、未知功能的伴随蛋白以及类似CRISPR的非编码DNA串联重复阵列，初步实验显示该阵列可表达为短RNA分子。 CRISPR先驱张锋评价该发现是AI智能体促进生物学发现的生动范例，相关预印本论文已公开发布。 新型酶系统ART的自主发现 在Anthropic团队仅给出检索新颖逆转录酶（RT）提示词的前提下，约950个Claude智能体检索了超过20万个RT，提取出3500个新候选系统并收窄至20个重点候选对象。其中一个智能体在巨型噬菌体基因组中，注意到一个异常逆转录酶旁存在肉眼可见的串联DNA重复阵列。团队将该系统命名为阵列相关逆转录酶（ART）。 系统特征与科学潜力 ART系统由逆转录酶、邻近的未知功能伴随蛋白以及间隔均匀的DNA重复阵列组成。初步实验表明该阵列可转录为一系列独特的短RNA，模式类似于赋予CRISPR可编程特性的阵列结构。尽管具体主要功能仍在进一步研究中，CRISPR先驱张锋表示，发现与逆转录酶相关的RNA重复阵列极具吸引力，展现了AI对科学研究的推动作用。 AI辅助假设与实验室验证流程 Anthropic在湾区设有标准分子生物学实验室，不接触人类病原体，所有湿实验均由人类科学家完成。研究流程结合了Claude Science与Claude Code：Claude负责阅读文献、检索未表征序列、撰写人类可读的假设报告并进行严格剔除；人类科学家则对通过评估的候选物进行表达与生化分析，并将评判标准反馈给模型以调整提示词。

*We’re introducing a new life sciences research group and laboratory at Anthropic. Our focus is on fundamental biology research using Claude: exploring datasets of DNA to identify uncharacterized protein families, generating hypotheses at scale, and testing them through experiments in the lab. This post introduces the team behind this work and shares early results in which Claude discovered a novel enzyme system with properties reminiscent of CRISPR, with only high-level direction from our scientists.*Many discoveries that have revolutionized biology and medicine started with a scientist noticing something odd in the staggering diversity of molecular machines found in nature. Restriction enzymes Today, we’re sharing early results from one of our first research programs, in which Claude autonomously discovered a novel enzyme system that is associated with an array of DNA repeats, a pattern reminiscent of CRISPR. Although we don’t yet know its function, the system that Claude discovered has a set of characteristics that have only ever been found together in a handful of other systems, all of which are programmable and perform operations like cutting, copying, and pasting DNA. Beyond CRISPR, which has already transformed science and medicine, several other such systems are now in development as promising tools. The system that Claude found is based on a reverse transcriptase (RT), enzymes that copy RNA into DNA. While this underlying RT, found in a jumbo phage, had been identified in previous studies, Claude appears to be the first to notice the system’s defining features—an associated array of non-coding DNA sequences and an additional accessory protein of unknown function. After reviewing the pre-print, Feng Zhang, one of the pioneers of CRISPR genome editing and a professor at MIT and the Broad Institute, said: *This is an exciting example of how AI agents can contribute to biological discovery. The identification of RNA-repeat arrays associated with reverse transcriptases is genuinely intriguing and merits further investigation. I hope this work encourages more scientists to explore how AI can support their research.* We gave Claude a prompt to search through a massive database of DNA sequences for interesting new examples of RTs. Our involvement was limited to the initial prompt and the lab work, while Claude agents combed through the database, investigated the distinct RT families, and used their own judgment to identify interesting candidates. After 21 hours spent searching this data by roughly 950 agents using 210 million tokens, one of the agents spotted something remarkable: a repeating pattern of DNA sequences that occurs next to the gene for an odd-looking RT. After further analysis and testing in our lab, we recognized that this pattern marked a previously uncharacterized enzyme system found in bacteriophages (the viruses that infect bacteria) that we call array-associated reverse transcriptases (ART). Our work to understand the primary function of ARTs is ongoing. However, we think it is important to share such findings early, both to demonstrate Claude’s capabilities and to give the broader community insight into what we’re working on. We have released a pre-print ([here](https://www.biorxiv.org/content/10.64898/2026.10.05.755809v1)) that discusses this in more detail. We are a team of scientists who have spent our careers exploring unusual proteins, and specialize in using computational approaches to systematically read DNA, interpret its evolution, and pick out biological systems for further characterization. Our research prior to joining Anthropic has helped to better understand the [evolution](https://www.science.org/doi/10.1126/science.aei0498) and [regulation](https://www.nature.com/articles/s41586-018-0557-5) of CRISPR systems, discover new [enzymes](https://www.nature.com/articles/s41586-024-07552-4) for next-generation [cell and gene therapies](https://www.science.org/doi/10.1126/science.adz0276), and build [tools](https://www.nature.com/articles/s41586-026-10176-5) for accelerating the identification of anomalies in DNA, such as human pathogenic variants. We are part of Anthropic’s life sciences organization, alongside teams whose work includes drug discovery, and training Claude in biology and chemistry. Our lab, located in the Bay Area, looks like a typical molecular biology lab. We do research that involves only the lower levels of the biosafety risk level (BSL-1 and BSL-2) and we do not handle pathogens that can infect humans. All of the lab work is performed by human scientists. Although we’ve experimented with using AI to accelerate lab work with initiatives like the [Model Hardware Standard](https://www.anthropic.com/news/model-hardware-standard-research-preview), this approach is less conducive to the sort of ad hoc workflows that are involved in our molecular biology research. Many of our workflows involve having Claude search through the vast collection of DNA sequences associated with proteins without a known function. One typical pattern begins with a survey of a given protein family. Claude reads the relevant literature and reproduces the established results from public data to check its methods. It then searches for family members or genomic neighbors that fit no described system, and writes a short, human-readable report for each candidate that proposes a function and describes the evidence supporting its claims. In follow-up analyses, Claude critically evaluates the evidence—typically most candidates are eliminated at this stage. A survey may end with a single candidate worth testing, or with none. When a candidate survives our review, we test it in the laboratory, expressing the protein in standard laboratory strains and characterizing it biochemically and structurally, with Claude helping to interpret the data. We do our work in [Claude Science](https://claude.com/product/claude-science) and [Claude Code](https://claude.com/product/claude-code), the same tools available to any scientist, and sometimes with a harness of our own that coordinates many Claude sessions running in parallel. Because Claude produces hypotheses so prolifically, the hypotheses themselves have become an object of study for us. With hundreds to thousands of candidate reports from a single campaign, we have been asking what distinguishes the proposals we judge worth testing from those we set aside. What we learn goes back into the instructions we give Claude and teaches it to mimic our own scientific taste. In the past few years, researchers have discovered many more reverse transcriptases (RTs), most of them in bacteria, where they act as part of the immune system. Nearly all RT families were found by genomic analysis, or genome mining, which requires researchers to search sequence databases for genes that no one has characterized, notice the unusual ones, and work out what they do. Claude agents gathered over 200,000 RTs, picked out 3,500 new candidate systems, and narrowed those to the 20 most compelling candidates that they analyzed to produce human-readable reports. For an expert scientist, this type of analysis can take weeks to months of work. During the course of its research, Claude noticed an unusual RT family and decided to examine it in greater detail. While combing through the raw DNA sequence near the RT, the agent exclaimed: “\[The DNA next to the RT\] is spectacular: I can see by eye a tandem repeat array … that's a CRISPR-like … repeat array?!” The system it found, ART, is found mainly in bacteriophages and consists of three parts: the RT, a partner gene beside it, and a long array of evenly spaced DNA repeat sequences. The repeat layout resembles a CRISPR array, which holds a bank of different RNA sequences that make CRISPR-Cas systems programmable biotechnological tools. Our first experiments show that the ART array is also expressed as a set of distinct short RNAs, suggesting that something analogous may be at play for this system. Further experiments are underway to determine how ART works, and we are sharing these early findings to show the community that Claude can autonomously detect anomalies and drive analyses to initiate biological discoveries. You can find more detail in our technical report ([here](https://www.biorxiv.org/content/10.64898/2026.10.05.755809v1)). We hope this work demonstrates the value of AI-driven hypothesis generation to the wider scientific community, and we would like to work with other scientists to extend this approach to a broad range of problems, in genomics and in other fields. If you have a proposal for a research question, we would like to hear from you. Features on AI-assisted discoveries, practical workflows, and field notes across the sciences.