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Unlock the future of agtech and CRISPR with this deep dive into the world of soybean innovation and next-gen crop defense! Matt Begeman, a key voice from Confluence Genetics, unveils how his team is driving breakthroughs in seed genetics and leveraging cutting-edge technologies like CasClear. From transforming the profitability and sustainability landscape for growers to exploring the epic potential of CRISPR-based antimicrobials and cell-specific cancer therapies, this episode journeys across the science and strategy shaping global food and health systems.

Listen in to discover:

• The intricate challenges and opportunities facing modern soybean growers
• How AI and advanced breeding accelerate development of nutrient-rich, high-value crops
• The story behind CasClear and its powerful implications for agriculture—and even cancer treatment
• Why data, partnerships, and strategic tech licensing are changing the game

If you’re passionate about the intersection of biology, technology, and agriculture, this episode is packed with thought-provoking insights you won’t want to miss!

5 Key Takeaways

Take your agricultural strategy to the next level with these essential insights:

1. AI-driven breeding models like CropOS can significantly accelerate soybean variety development and optimize desired traits—embrace technology to boost your crop outcomes.
2. Creating higher-value soybean products with specialty traits unlocks premium markets for growers—seek out partnerships to increase your profitability per acre.
3. Gene editing and CRISPR-based innovations, such as CasClear, are expanding possibilities for crop protection and quality—stay informed and engaged with cutting-edge solutions.
4. Gathering and leveraging high-quality, connected sequence and phenotype data is key to successful breeding and product innovation—invest in your data strategy.
5. Strategic collaborations and technology licensing can help expand the reach of impactful platforms—consider partnerships to amplify innovation and business growth.

Memorable Quotes

"So if we could take our CasClear technology, design it specifically for their cancer, deliver it to that individual, and basically deliver cell-specific chemotherapy where it only destroys the cancer cells and leaves all the normal cells intact. That's the conceptual idea we've built with CasClear in the oncology space."

"Our goal is to enable as many different companies to use this technology as we can because I can't work on soybeans, antimicrobials, and oncology all at the same time. We've really got to partner with other companies to make this successful."

"If you have decades worth of phenotype data but you've never sequenced your populations or understand your population structure, you're also kind of stuck. You've got to really pull both of these together to enable those AI tools to really drive your breeding organization forward and make better products at the end of the day."

Connect with Matt

LinkedIn: https://www.linkedin.com/in/matthew-begemann/

Resources Mentioned

confluence.ag – https://confluence.ag/

castclear.com – https://castclear.com/

University of Missouri – https://missouri.edu/

University of Wisconsin–Madison – https://wisc.edu/

University of Utah – https://utah.edu/

UC Berkeley – https://berkeley.edu/

Benson Hill – https://bensonhill.com/

CropOS by Benson Hill – https://bensonhill.com/cropos/

ChatGPT by OpenAI – https://openai.com/chatgpt

Anthropic – https://www.anthropic.com/

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So if we could take our CasClear technology, design it very specifically

for their cancer, deliver it to that individual, and basically

deliver cell-specific chemotherapy where it only destroys

the cancer cells and it leaves all the normal cells intact. And

that's the conceptual idea that we've built with CasClear in the oncology space.

So Matthew, thank you for joining us today. To kick off this

conversation, can you present a little bit about you, your background,

and how you got involved in Confluence? Yeah.

So I'm Matt Begeman. You know, I've been involved in agriculture for quite

a long time. My family actually farms soybeans in Missouri. And so,

you know, we're end users of the product. You know, always been interested in applied

sciences. So I did my undergrad at the University of Missouri

working on biochemistry and microbiology. And then I went up to Wisconsin and got

my PhD in microbiology and worked in a chemical engineering lab.

really focused on, you know, how can we use the energy of the

sun to create commodity chemicals? And that world honestly fell

apart because of the fracking revolution and chemistry got really cheap. And

so then I ended up jumping into the agriculture side and I worked at a

company called Benson Hill for about 10 to 12 years. And there

we worked on trait discovery to improve plants.

We built out gene editing tools to do it and we built out AI tools

to enable people to use AI for plant breeding to increase

productivity of plants. And then we got really focused on soybeans. Soybeans

at the end of the day are the most efficient source of protein in the

world. It's really hard to beat soybeans. At the end of the day, the

world doesn't seem to be short calories, but we are short protein. There's

increasing demand for protein and it is just an excellent source of protein. But

it's not perfect. There's a lot of improvement to be made in soybean. And at

Confluence Genetics, which bought Benson Hill out of bankruptcy a couple or a year

ago, We're focused on improving soybeans. Commodity soybeans are

great. There's a system built around it. But if we can make soybeans a little

bit better, or even a lot better, we can have a dramatic impact on the

entire agriculture supply chain, which helps everybody from a sustainability

perspective all the way through an end consumer of getting a better product for a

better price. And so I've been in the technology space for a long

time. I've been in the agriculture space, and my career is really focused on

Can I take discoveries in the lab and work with a commercial partner on the

end to get it all the way out of the lab, all the way out

of research and into somebody's hand who gets to use that product at the end

of the day? Interesting. And for those who are

not aware, what sort of challenges are faced

by soybean growers? You know,

it's a commodity crop, and it's a global commodity crop. And so if you think

about a soybean farmer in the United States, Their competitor

is their neighbor down the street who's also growing soybeans. But there are other competitors

in South America and around the world. And it's a global supply chain.

And soybeans need to go to Europe, they need to go to Asia.

And obviously, they get turned into soybean meal and oil in the United States and

fed to animals. And those prices are constantly fluctuating. And then

you've got, you know, external pressures, whether it's the weather or

something else that has an impact on your crop. And so as a soybean

grower, you're gambling with your net worth every single year, which

is really stressful. And there's so many technologies out there which you could be

using, and you've got to make a decision on which technology should you use

and what's going to have the best impact for your operation. And so, you know,

farming is a challenging job. And it continues to get harder as

the global supply chain changes. But if you talk to growers, you

talk to farmers, they're ready for the challenge. And they're looking for, you know,

companies like Confluence Genetics, to provide them with new technologies

so that they can get a better product so that they can make more money

on their acres, which is what they need at the end of the day to

keep their operations alive and growing. And we're seeing also a lot of,

maybe not a lot of, but some growers also turning away from other

crops that are resource intensive into soybean, turning

away from corn into soybean, things like this. Is this something that

you're seeing as well? You know, I would, I would say that the

decision has gotten more challenging than it used to be. It used to be a

more straightforward decision on a corn-soy rotation.

And then do you, you know, you put some winter wheat in there, especially in

the United States? I think with fluctuating commodity prices, it becomes

a much more challenging decision. And there's, there's a lot more strategy

in terms of what are you going to grow this year? How do you plan

for next year? So we do see more people interested in soy, and we

see more people interested in doing specialty soy products that give

them a premium. So at the end of the day, we sell seed,

and the growers that work with us end up, you know, in some sort of

relationship with another entity, where they get a premium for the product that they

generate. And so they get to make a little bit more money than commodity soybeans.

And so really, you know, that's how we help the grower is we create a

more valuable product. And they get to sell, you know, their soybeans

at the end of the day for a higher price, because it's a more valuable

product. Whether it's going into aquaculture, human food, it's going

into dairy, or it's going into poultry, there's a premium market for them and we

unlock that. Interesting.

Interesting. And now to talk about your company,

Confluence Genetics. Recently there's been some updates

on your platform, CasClear. Before we jump

on that news, can you explain as well what CasClear is?

for those who are not aware? Yeah, so CasClear is

a CRISPR platform. It's not a gene editing tool. And so I really want to

differentiate that. So traditional gene editing, it's a CRISPR

nuclease, cuts DNA normally, and it has a guide RNA that tells

it where to go in the genome and it makes a cut. And you can

do that to, like we've done, is we improve the quality of soybeans through gene

editing, right? You can use gene editing in the human

space for different human applications, human

therapies, but we've discovered something a little bit different. And so what we found

in our lab is we thought we had discovered another CRISPR gene editing tool,

but rather than doing gene editing and just making a single cut, after

it finds its target and it does make a cut, what it does is it

changes the shape of that nuclease and then it indiscriminately chews up

the DNA and the RNA of that cell and it destroys that cell. So

when we first discovered this in the lab, it was a challenge at first because

it was hard to work with. Because we were growing it in bacteria and our

bacteria were dying. And we quickly pivoted and said, you know what, we can use

this as an antimicrobial. So it maintains the target specificity

of CRISPR systems, right down to single base pair specificity. And now

you can kill a bacteria with it. And then we started to ask, well, you

know, could we kill a higher level organism, like something like a yeast? And

yes, it can do that. And now you start to think about all the broad

applications of it. So Or in agriculture, could we use it to kill plant

pests? And so that's something that we've been working on in our lab

is, can we turn this into a defensive trait for agriculture?

And we filed some patent applications and we've made good progress on there. Could you

use it in antimicrobials? I think absolutely. And then the

other area where you could potentially use this Cas-Clear technology

would be oncology. So at the end of the day, cancer is

a mutation that pops up in somebody's cells as they're growing. They're called

oncogenic mutations. With modern precision medicine, we're actually

very good at going to a patient and sequencing their cancer

and understanding what's the exact mutation that's causing their cancer.

So if we could take our CasClear technology, design it very specifically

for their cancer, deliver it to that individual, and basically

deliver cell-specific chemotherapy where it only destroys

the the cancer cells and it leaves all the normal cells intact. And

that's the conceptual idea that we've built with CasClear in the oncology space.

You know, we've had success in our lab and we've recently seen multiple

universities, the University of Utah and UC

Berkeley and Jennifer Doudna's lab. They've also been able to get this work in many

different types of cancer cells, whether it's lung cancer, liver cancer,

or, you know, generic lab cells that they've been growing. And

they've most recently been able to demonstrate that it works in a mouse model.

Wow. Yeah, it comes to show that plants are not that different from

humans. At the end of the day, it's the same, it's the same

technology that can get applied to different things, right? So, you know, the original gene

editing technology like Cas9 can be applied to many different things.

CasClear is in the same boat. It's a fantastic technology. And

our goal is actually to enable as many, you know, different companies to use this

technology as we can because we can't, you know, I can't work

on soybeans and antimicrobials and oncology all at the same time, right?

And so we've really got to partner with other companies to make this successful.

I was wondering, as a company, how would you target? Would

you still focus solely on soy, or would you also

expand into other crops or maybe other areas such as

oncology and so on? What would you offload to other

companies, or at least partner with them,

etc.? The vast majority of the company, including

myself, we're very much focused on leading the way for

high-quality soybean genetics. And that's our core

competency. And that's our core focus area. And that's where the vast majority of the

people in the company are focused on. We've got a couple of people

that are working on gene editing in soy. For quality traits to further

improve soybean quality. And they're also working on this CasClear technology

to get the underlying chemistry much more efficient

and ready to go for different use cases and applications. And so how

we envision, you know, working with other companies in that space is we're the

technology provider at the end of the day, we can license the technology, we can

do co-development deals where we can leverage our expertise on

optimizing CRISPR chemistry, which we're very good at. And we can leverage their

capabilities, which is going to be on the oncology side and the delivery

side. At the end of the day, it takes a community to deliver a

product, whether it's in agriculture or in oncology. And on the oncology

space, there's usually, you know, some kind of cargo and a delivery mechanism, and we're

going to have to partner with somebody on the delivery side. And so we're very

open to understanding how we fit within the ecosystem and

where the technology provider and the developer. kind of becoming like

the AWS of— Yeah,

yeah. At the end of the day, you know, it can be a, it can

be a generic technology, and we are focused on really making it better. And

we enable the end user to be really successful with the product as well.

Okay, interesting. Now to come back on the axe side, since this is

our area of focus, what plan

defense applications of your platform

would look like. Yeah, the question behind this is like, would

that go through the same— I know it's very different and it's very

also a hot topic and so I want to talk about, but is it the

same GMO gene editing regulatory pathways?

I think you can go through a GMO regulatory pathway to get this

across the finish line. Conceptually, if you had CasClear embedded in

a plant, And it had specific targets for a

bacterial pathogen, such as a Pseudomonas, a leaf blight. If it

had, you know, a specific target for a fungal pathogen, you could potentially

have a target for something like a nematode, a higher-level organism that you

could constantly be updating. And so yes, that would be through a traditional GMO

process. As you know, that's kind of a longer road to get across the finish

line. We got a lot of work to build out efficacy of the product, but

that's kind of our focus from a plant defense perspective.

Okay. Even if from a regulatory standpoint, there's been some updates, at

least in some parts of the world. So I don't know whether you guys are

only focused on the US or you're also involved in Europe, but

at least like there's been the new genomic technique frameworks in Europe and so

on. So I guess, yeah, to kind

of go back to this, CasClear is a CRISPR technology. It's

not a gene editing technology. So to use it for defensive traits, it would

really be a full GMO pathway. On the other side, where we're just

doing gene editing in soybeans for quality traits, we do see that market

start to open up, especially some of the changes in Europe, kind of going back

to soybeans are a global commodity. If you're working on

gene-edited soy, you really got to get through a regulatory process

around the world. And that's really speeding up and opening up, which I think is

fantastic. And it's going to open up a lot of opportunities in the agriculture

space. As, you know, as somebody who's embedded in the technology

and also works on the commercial side, it's frustrating for me to see

we've been sitting on gene editing technology for over a decade. And there's just not

a lot of products out there, even though it's a great technology. You know, there's

times when it's regulatory that's really holding that back. So if you look at

our soybean portfolio today, we have a lot of quality traits, and they're not

gene edited. They're from natural genetic variation that we

pulled from, you know, genetics from all over the world. And, you know,

we've combined them through breeding. And that's also a decade-long

activity, which gives us a bit of a moat, right? Because, you know, pulling those

soybean genetics together for different quality traits for animal feed and

human food applications, but it takes a long time. And we're in

a really good spot now where we have pulled those together. And we can leverage

our AI breeding to make it even better. But when we think about new traits

flowing in, it would be fantastic if gene editing was more available and opened up.

Yeah, actually that was one of the questions I had as well, is obviously

recently we've been talking about AI at every single

sauce, kind of. How does that impact the development

and the use of your platform?

Yeah. So, you know, we've been using AI to do breeding for a while

now. It's different than the new AI models that have come out, the

large language models. We certainly use that in-house for some

work, but our AI breeding models are built on a

slightly different platform. And the idea is if you take

a soybean and you sequence it, and you don't even need a high level of

sequence depth, from that sequence, we can predict its

yield to a certain degree. And we are very good at predicting its quality

traits, especially protein and oil and carbohydrate profiles.

And because we can do that, we can leverage

sequencing through our breeding program. So we have a tool called

CropOS. And CropOS can look at all of the different soybean

varieties we have. And our breeder can go in with their

specifications, just like you're developing software. I want a

soybean variety that grows at this maturity group to grow in, you know,

Central Iowa across to Illinois. I want it to be high

protein. I need it to have low anti-nutrients for poultry.

And here's some other properties that I want. And CropOS will go in and

look at all of the different germplasm we have. And it'll run

millions of simulations, predict the best soybean

varieties to cross, and then also provide our breeders with a

recipe, a series of instructions on not just how to make the crosses,

but How many progeny downstream do you need to look at in sequence and at

what depth? And then how do we make selections down the line? And our team

can execute on that using sequencing along the way to run

predictions on all of those progeny. So when we take our

material out to the field, we have a really good idea of its performance,

especially on the quality trait side. And we're really just looking for what

are the best yielding varieties that are still going to hit our product specs. And

that's how we're leveraging AI and still using field breeding at the end of

the day to do kind of those final measurements of yield so

that we can deliver a valuable product. And what is the impact

in terms of amount of time that's

taken to develop such a thing? Yeah, there, I mean, there's a really

big speed game here. If you're doing traditional breeding and you're making

crosses once a year, maybe twice a year, and, you know, in the

field in North America, and then in South America, development of a new soybean variety

can take 8 to 10 years. You know, we're looking at closer to 6 years

with our technology. Other companies are also, you know, very aggressive

on using an AI platform and using indoor breeding like we

are. The difference is, is it's less so on the AI

platform. It's very similar to a lot of these LLMs we're seeing with, you

know, Anthropic and ChatGPT and all these others, right? Everybody's got great

models. But a big differentiator is what is the strategic data

that you're feeding that model to drive the decision? So everybody can build

an AI model in this space, but who has access to

strategic data? And in our case, it's, we've got the sequence data

and we got the phenotype data. So the protein, oil, carbohydrate profiles

yield on really diverse germplasm around these quality

traits. And our germplasm looks very different than the other companies.

And so we've got, you know, a decade worth of breeding data and all

of this phenotype data, and that enables our models to be really good

at predicting things like protein and oil and quality

composition. Whereas other companies, they just haven't generated that data because they

haven't valued the quality traits. Yeah. I mean, data is the number

one, is the new gold, I guess. Yeah. You've got to have data and it's

got to be high quality data and it's got to be connected. So if you

have a bunch of sequence data, but You don't have any of the phenotype data,

there's, there's not much you can do. If you have decades worth of phenotype data,

but you've never sequenced your populations or understand your population

structure, you're also kind of stuck. You've got to really pull both of these together

to enable those AI tools to really drive your breeding organization forward

and make better products at the end of the day. That's our real goal.

Yeah, absolutely. In terms of

Now talking more about like growers adoption and so on,

how has been the feedback provided by growers

on using these, these crops? The

feedback from growers is they've been looking for alternatives

to commodity crops for a while. If you talk to a lot of growers,

they've got limited options in terms of types of crops that they can

grow. They've got limited options where they can sell it. And then

they've got limited options if they want to get a premium for that product. You

know, an example is something like organic. Organic is quite hard to get into.

There's kind of a 3-year period where you've got to go through that process before

you can really capture value off of it. So when we talk to

growers, you know, if we can give them something where

they're going to get a premium off of that variety, yield-wise, it's very

similar to other commodity options they can get. And we've got

herbicide-tolerant varieties coming out in the next couple of years, which make

it even easier for a grower to adopt our technology because they don't have to

necessarily change their agriculture practices. They can grow these

varieties, they can be in an identity preserve program

and get a premium for that product. And so it starts to make a lot

of sense for them if they don't have to change their operation too much. And

they can capture some extra value on the back end.

Interesting, interesting, very interesting. Now, in terms of looking

ahead 5 years out, do you believe that Confluence would

still primarily be a soy genetics company, or do you

think it will become a larger group with different divisions, each focusing

on all the potential applications that that platform has?

We've got a lot of work to do in the next 5 years in soybeans.

Soybeans are a big crop. In the United States alone, there's 85

million acres. A lot of that goes into animal feed. We

feel like we're really well positioned to capture as much of the animal feed

market as we can. And so we're going to be really focused on capturing

as much of this animal feed market. We also work in oil quality

with the Hyolaic oil product. We have a lot of growth opportunity on

both the Hyolaic side for Human food, but also dairy

cows, high oleic soybeans are really taking off. And then on the animal feed

side, the poultry market is huge. And we provide a lot of value

in the poultry market. And so we've got a lot of work to grow there.

And so in able to do that, we've got a lot of work to do

to get new varieties out, get the herbicide tolerance traits out there,

and really grow our maturity zones so that we can get to more

farmers in the US. And so if you look at that 5-year roadmap, We're going

to be busy in the soybean space, which is fantastic. You know, on the technology

side, we're going to continue to develop those CRISPR technologies. And our goal is

to license those out. If you look at these latest papers, yes, you

know, they've used CasClear in test tubes on cancer cells and it

works really, really well. You put it into a mouse and it

works, but we haven't fully cured cancer in a mouse yet. So

that means we've got some work to do to make the underlying technology

better and build a better vehicle to package it in. And I think there's

a little bit of work there. And then hopefully we can solve those problems.

And now we can hand off this asset to somebody else who can really go

turn it into an oncology therapy, which would be great for us

as the technology provider, because at the end of the day, we want our

technology out there. You know, we get a, we get a license royalty on the

back end, which is fantastic, but then we can help out another group of

people. At the end of the day, not everybody knows a farmer. Everybody eats, but

not everybody knows a farmer. Everybody's been impacted by

cancer, whether it's a family member or a friend, and

you've gone through the pain of dealing with that situation. So

if we can have an even bigger impact on both the food side and the

human health side, and even those are obviously linked together because what we eat is

important too, I think we'll have an even bigger impact on the world. And if

the plant defense applications pan out, does that ever

loop back and strengthen the core soy trait business?

Absolutely. Yeah. So our plan there would be to really focus on it for

soybean plant defense. When we think about other areas where plant defense is a

big deal, obviously your major row crops, yes, corn and

soy, there's a lot of money to be made on defensive traits because they're constantly

being bombarded with plant pathogens. A lot of other crops

deal with pathogens quite a bit. Potato is a great example where it gets

sprayed with pesticides a lot. A lot of your produce gets sprayed with

pesticides a lot, same with cotton. So on the plant defense side, I think

there's, there's kind of growing opportunities where we could get into some other spaces as

well. But we would really need to partner with other organizations that

know their pathogens really well. And again, we can work with them on being a

technology provider. And if we make our underlying technology even

better, they're going to be in a much better situation to onboard

that technology into their group and be successful.

Fantastic. Well, Matthew, thank you. Thank you for your time

and for answering all the questions. If people want to connect with you or

learn more about Confluence Genetics, how can they do so? You know,

confluence.ag is a great place to start if they're interested in our agriculture

business and what we're doing in the soybean space. We've got a lot of content

up there on our soybean varieties and our animal feeding studies showing increased value

in poultry, aquaculture, and dairy. If people are

interested in the CastClear, castclear.com is a great

place to go. And at both of those websites, they can either find

my contact information or contact information for the company, and they

can reach out to us to learn more. Okay, perfect. Well,

Matthew, thank you again. Thank you for your time. I appreciate it.