Gallium cannot be used as a Trojan horse to fool Iron-selected bacteria

This post is by NCAT postdoc Akamu Jude Ewunkem, faculty Misty Thomas, grad student Sada Boyd, and faculty Joseph Graves Jr.

Antibiotics have heretofore been used as therapeutic agents (Butler et al., 2017). However, bacteria are increasingly developing resistance to these therapeutic agents. Due to this continuum of resistance evolution there has been a stagnation in the development of novel antimicrobial agents to treat multidrug-resistance organisms. However, alternative therapeutic options are currently being exploited for treatments. Iron acquisition is an alternate target of antimicrobial agents.

Iron is an important micronutrient for virtually all living organisms. Iron is involved in a wide variety of important metabolic processessuch as photosynthesis, respiration, the tricarboxylic acid cycle, oxygen transport, gene regulation and DNA biosynthesis (Weinberg, 2009). In bacteria, iron influences cell wall composition, intermediary metabolism, secondary metabolism, enzyme activity, and host cell interactions. Bacteria use surface proteins, heme group and siderophores for acquisition of iron. The competition for iron between host and bacteria is so important that many multicellular organisms have evolved defense mechanisms that sequester iron away from pathogenic microbes.

Gallium is a transition metal element, and has a similar ionic radius to that of iron. Thus, gallium can efficiently compete with iron for binding to iron-containing enzymes, transferrin, lactoferrin and siderophores. Gallium is used as a trojan horse to iron-seeking bacteria. Invading bacteria are tricked, in a way, into taking it up. However, while the binding of iron to a protein promotes protein function, the substitution of gallium for iron in a protein usually disrupts its function and may lead to adverse downstream effects in cells (Choi et al., 2017).

Our laboratory is evaluating the fitness of iron resistant bacteria in gallium. We utilized experimental evolution to create 12 iron (II) and 12 iron (III) selected replicates in Escherichia coli.  These cells had been selected in excess iron for 28 days. Within each selection regime, 5 had no history of silver resistance and 7 were derived from Agresistant replicates (Tajkarimi et al. 2017).  The control cells had no history of either iron or silver resistance. Fitness of these replicates was evaluated in the presence of increasing concentrations of Gallium (III) nitrate.  Our results indicated that bacteria selected in Iron (II) as well as Iron (III) showed a significantly superior 24 hour growth in Gallium nitrate compared to the controls (Fig 1 and 2).

Fig 1: Twenty-four-hour growth curve of Iron (II)-Selected E. coli in the presence of increasing concentrations of gallium (III) nitrate. Fe2+=Iron(II)-selected bacteria. Fe2+Ag= Iron (II)-selected bacteria with silver background.

Fig 2: Twenty-four-hour growth curve of Iron (III)-Selected E. coli in the presence of increasing concentrations of gallium (III) nitrate. Fe3+=Iron(III)-selected bacteria. Fe3+Ag= Iron (III)-selected bacteria with silver background.

For example, for the iron (III) resistant populations there was virtually no reduction in growth from 60—1000 mg/L of gallium, while for the controls growth was completely eliminated at 1000 mg/L. Interestingly, gallium was also very toxic to the ancestors of iron-selected cells with silver background (i.e. silver selected bacteria) (data not shown). Whole genome sequencing of our iron-selected bacterial cells demonstrated that mutations occurred in genes that confer anti-transition metal stress resistance. Examples of these genes include fecA (ferric citrate outer membrane transporer), rho (transcription termination factor), fur (ferric iron uptake regulon transcriptional repressor), murC (UDP-N-acetylmuramate: L-alanine ligase), dnaK (chaperone HSP70), tolC (transport channel), and nusA (transcription termination/antitermination factor).

In addition to whole genome sequencing, we utilized Nanostring technology to examine gene expression profiles of 50 genes we determined to be involved in iron metabolism or general metal resistance. We found striking patterns of expression difference in the presence of excess iron for genes: regulated by fur (ferric iron uptake regulon transcriptional repressor), involved in cell wall synthesis, general metabolism, transcription, transport, and transcription regulation.  Generally, genes in these categories in the iron resistant bacteria were significantly up-regulated, while these same genes were significantly down-regulated in the controls.

Thus, we hypothesize that the genomic profile and altered gene expression patterns of our excess iron resistant E. coli has also changed the way they interact with the iron analog gallium. Either these mutations reduce the rate that gallium enters the cell, increases the rate in which it is effluxed from the cell, or alter the targets of gallium toxicity once inside the cell.  These results suggest that gallium cannot be used as a Trojan horse to fool iron-selected bacteria, as there survivorship in the presence of increasing gallium suggests the capacity to rapidly evolve resistance to it. We will test this idea in subsequent experiments.

References

Butler, M. S., Blaskovich, M. A., & Cooper, M. A. (2017). Antibiotics in the clinical pipeline at the end of 2015. The Journal of antibiotics, 70(1), 3.

Choi, S. R., Britigan, B. E., Moran, D. M., & Narayanasamy, P. (2017). Gallium nanoparticles facilitate phagosome maturation and inhibit growth of virulent Mycobacterium tuberculosis in macrophages. PloS one, 12(5), e0177987.

Weinberg, E. D. (2009). Iron availability and infection. Biochimica et Biophysica Acta (BBA)- General Subjects, 1790(7), 600-605.

Tajkarimi, M., Rhinehardt, K., Thomas, M., Ewunkem, J. A., Campbell, A., Boyd, S., … & Graves, J. L. (2017). Selection for ionic-confers silver nanoparticle resistance in Escherichia coli. JSM Nanotechnol. Nanomed, 5, 1047.

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High school phage hunters: an experiment to encourage young scientists

This post is by MSU postdoc Sarah Doore, with contributions from Dr. Kristin Parent and Mr. Kevin Schrad

For the last couple years, our lab at MSU has been advocating “phage hunting” as part of the biology classroom experience. Bacteriophages—”phages” for short—are viruses that infect bacteria. To hunt phages, all you have to do is think about where a phage might be (usually anywhere you can find bacteria), scoop up a handful of water or dirt, then test your sample to see whether it infects certain strains of bacteria. Phage hunting is a great way to get students thinking about the microbial world and to help them relate to science and the scientific process.

I’ve written about a few of our adventures here and here, but thanks to funding from the National Science Foundation, we provided equipment and expertise to a Nebraska high school, Lincoln Southwest (LSW).

Jason Schrad explaining some of the lab techniques to the high school class

Students getting ready to check their samples for phage. Can you spot the class mascot?

This past April, my labmate Jason Schrad and I visited LSW in person. We helped our teacher-partner, Mr. Kevin Schrad, set up the equipment and walked him through the procedure. We explained bacteriophages to the students, discussed where they might be found, then went out and collected some samples from the local environment. We then worked with them to plate their samples and analyze their results. We did this for two classes for a full week, moving through each step of the scientific process along with them.

Spoiler alert: we didn’t find many phages.

This was a huge surprise to everyone, considering how many we found last semester. But we all thought the experience was awesome—phage or no phage! And hey, that’s how science goes sometimes. You always learn something from your experiments even if your starting hypothesis didn’t turn out to be 100% accurate.

Mr. Schrad said, “The Phage Hunting Experiment is a huge success for my classes. My students enjoyed doing what they called ‘real science.’ I know it sounds funny but they liked using the ‘real science’ equipment, especially the vortexers. [side note: evidence for this claim is here] The students enjoyed the hands-on experience and working with real scientists. They enjoyed being able to see the outcome of their work even if they didn’t find any phages.”

Another teacher at the school, Mr. Charley Bittle, was enthusiastic to meet us and see the process. Now he’s going to incorporate phage hunting into some of the other biology classes at LSW.

Mr. Schrad getting a sample from Iggy, the classroom iguana.

Partway through the week our lab leader, Dr. Parent, did a Skype session with both classrooms. This gave the students a chance to explain what they’d found and to ask more questions about a career in science.

Of the experience, Dr. Parent said, “One of the most profound things I experienced was when the girl in the second section who asked me: ‘what happens if scientists mess up?’ I started thinking that a student’s entire focus up until graduate school is to get the answer correct (at least in most STEM courses). So the idea that a hypothesis could be wrong, or that sometimes we don’t really know how to do it right the first time, is something we should prepare students for.

“Fear of not being 100% perfect is the killer for successful science. It’s good to teach the students that not everything works like the positive control every time and that’s ok (actually, troubleshooting can even be part of the fun). Negative results are sometimes very interesting, and we often need to re-evaluate our models/predictions, which means redesign and retesting.”

But you don’t have to take our word for how great this experience is. At the end of the semester, the students filled out an exit survey, which pinpointed what they found most interesting and valuable in the class. Here are three of the questions from the survey and a sampling of the responses:

Describe how the phage hunting experience made a difference in your understanding of biology and science in general:

“It helped me understand what it truly means to ask questions and test things in science.”

“It made it more exciting and made us able to interact with [microbial] wildlife that we never would’ve interacted with before.”

“This made me think about how there could be viruses in almost anything in the world around you.”

“It opened my mind”

“It gave us a chance to look at what real scientists do.”

What long-term benefits could the phage hunting (viruses) project provide to you?

“It gives me something to look back on in the future and make me remember all the things I saw that I’ve never seen or knew existed before.”

“I think it could provide a better understanding of the micro level of this planet.”

“It could show me a possible career to go into.”

“It could help you to see if you want to go into that kind of science thing.”

“It made me more interested in it.”

What skills have you gained from the phage hunting project that may help you become a better student, scientist or citizen?

“It made me realize that being patient brings good things” – similarly, “to be patient while waiting for the results.”

“I learned how to work with others in my class, how to investigate things, and how to use the equipment.”

“It made me think more deeply about questions and to go out and search and experience.”

“Always taking notes on what I did so that if I were to go back to it in like 12 months that I would know what I was doing.” [totally agree with this!]

We’ll keep hunting phage in the future, though next time we could encourage students to sample from their own home or neighborhood and then compare that to what they found at the high school. The more classes we do this with, the more we’ll refine our methods and strengthen the partnership between university and high school.

“As we go through the techniques more it begins to be a bigger part of our curriculum,” said Mr. Schrad. “Having real scientists leading the project and actually being part of the process has a tremendous impact on how the students view the project. If we spark the interest to go into science of just one student it is a worthy accomplishment.”

Interested in trying this for your college or high school class? Feel free to talk to us on Twitter @Phage4Lyfe or visit the Parent lab website, which includes video protocols for phage isolation.

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In the Light of Evolution: Connecting Genotype to Phenotype and Fitness in an Introductory Biology Class

Katie Dickinson

This post is by UW research scientist Katie Dickinson

It was through the [Bio180 CURE] class that biology truly came to life and I felt that our time in [the] lab was interesting and relevant to our world today. The large lecture halls felt smaller as our table group grew closer together…”  Former Bio180 CURE student.

I am helping to develop a set of labs that enables undergraduate students, early in their academic career, to experience what it is like to do research. Ultimately, we aim for this CURE (Course-based Undergraduate Research Experience) to be woven into the Introductory Biology series (BIOL 180 and BIOL 200) at the University of Washington. In addition to trying to make research accessible to large numbers of students, students are able to observe evolution in action to better understand a global health crisis, antibiotic resistance.

In this blog I wanted to provide a general overview of the Intro Bio CURE lab series. Students use bacteria to investigate the evolution of antibiotic resistance at the population level and connection to cellular/molecular mechanisms.

Students hard at work

In the first set of labs, students expose E.coli to specific drug regimes, which select for resistant mutants. These mutants, along with a sensitive ancestor, are transferred daily in drug-free media for several weeks. Samples of each isolate are frozen down enabling students to make comparisons between the progenitors (from the beginning of the transfers) and the descendants (from the end of the transfers). Then assays are done to determine competitive fitness and the level of drug resistance of each isolate. The resistance level will be measured in two drugs enabling students to gauge whether they see evidence for cross-drug interactions; where resistance to one drug (the drug in the Petri dish that was used to isolate the strain) confers increased or decreased resistance to another drug. These labs highlight evolutionary phenomena at a population level.

Alumni students assisting with lab prep

In the second series of labs, students will analyze the products of their own evolution experiments (evolved bacterial isolates from the first course). Activities include: PCR/gel of a candidate gene, DNA sequence analysis, exploring protein sequence and structure analysis. The goal is to enable students to trace genotype to phenotype at the cellular level, and connect evolution to molecular biology.

Experimental Overview Schematic

Lab Activity Key Concepts
Lab1 Screen for resistance by spreading a sample of bacteria on Petri dishes with antibiotics and without. Natural selection, mutations, antibiotic resistance, sterile technique
Lab 2 Pick resistant mutants (and a sensitive isolate as a control), freeze down a sample and begin serial transfers in the absence of drug. Experiment design, fitness, the cost of drug resistance, evolution and population dynamics

 

Lab 3 & 4 Calculate relative fitness with mock data, learn how to determine a minimal inhibitory concentration (MIC) value, use R/Rstudio to graph and gauge significances. Serial transfers continue. Basic statistics, graphing, introduce cross-drug interactions (collateral sensitive/resistance)
Lab 5 Serial transfers end. Competition and MIC assays comparing the progenitors to their descendants Relative fitness, Levels of drug resistance, importance of collaboration
Lab 6 Data analysis, suggest future research Data interpretation, determine if there is evidence for a fitness cost associated with resistance, compensatory mutations, reversion, look for collateral effects
Lab 7 PCR, gel electrophoreses, sequencing Central dogma, genetic techniques
Lab 8 Analyze sequencing data DNA sequence analysis, identify mutations, translation, evolution, genotype
Lab 9 Protein structure Resistance mutation effect protein structure, enzyme function, phenotype and fitness.
Lab 10 Poster presentation Integrate connection between genotype, phenotype, and fitness. Scientific communication, collaboration

Competition Petri dishes and MIC microtiter plates

Last year we ran several pilot classes (single lab sections with 24 students). This winter quarter we scaled up, four randomly selected BIOL 180 lab sections swapping out the tradition lab material for the CURE modules. Currently, three BIOL 200 sections are continuing the CURE labs this spring quarter. Throughout the Intro Bio CURE labs, students are collaborating and communicating to collect and analyze their own data and propose follow-up experiments. In addition, students are introduced to career-transferrable skills.

Presently, data is being gathered on student outcomes. We are specifically measuring: core concepts, competencies, and affect. Are students gaining a better grasp of evolution via natural selection? Are they able to connect genotype to phenotype to fitness? Is there evidence for improved understanding of the experimental process, and how to gather and interpret data? Do students gain an appreciation for the importance of data visualization, statistics, scientific communication & collaboration? Does the Intro Bio CURE series enhance a sense of belonging in science/college and does this translate to retention in STEM fields? Do students identity as scientists? Are we successfully enabling students to cultivate a positive attitude towards value of research and practice of science?

What is next?

If outcomes are looking promising, we plan to go forward with scaling. By winter 2019 all students enrolled in the UW Introductory Biology series will be provided with the opportunity to engage in authentic research experience, serving roughly 2000 students per quarter!

 

 

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Congratulations to Prof. Percy Pierre, Chair of the BEACON Diversity Steering Committee

On April 10, 2018, BEACON’s own Prof. Percy Pierre, Chair of the BEACON Diversity Steering Committee and contributor to BEACON from its earliest proposal days, was honored with the Historical Leader Award of the MSU Black Faculty, Staff and Administrators Association (BFSAA). BEACON’s Business Manager, Connie James, who is Recording Secretary of the group, was on hand to describe to the group some of Percy’s most significant contributions.  His distinguished career has spanned serving as a White House Fellow, where he was deputy to the Assistant to the President for Urban Affairs; as Dean of Engineering at Howard University; Assistant Secretary of the Army for Research, Development and Acquisition, and later Acting Secretary of the Army; President of Prairie View A&M University; Vice President for Research and Graduate Studies at MSU, and Professor of Electrical and Computer Engineering at MSU.  In the latter role, he has mentored over 200 minority graduate students to degrees in Engineering, the accomplishment of which he is most proud. Dr. Pierre was a principal architect of the national minority engineering effort, co-chairing the 1973 National Academy of Engineering Symposium that launched the effort. He served as the program officer for minority engineering at the Alfred P. Sloan Foundation, where his efforts resulted in funding of many minority engineering organizations, including NACME, GEM, MESA, DAPCEP, and SECME. He was elected to membership in the National Academy of Engineering, and has received many other awards and honors.

Percy’s wisdom and vast experience have helped to shape BEACON’s diversity efforts to be among the most successful of any of NSF’s Science and Technology Centers. We all owe him a debt of gratitude for the positive and supportive atmosphere that pervades all of BEACON today.

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Exploring the evolution of troglodytes?

This post is by MSU postdoc John Phillips

Some of you may be familiar with the term ‘troglodyte’, which is a somewhat old-timey derogatory term for an unintelligent person. The Greek root troglo- means “cave” so a troglodyte is a cave person. While we use(d?) this as an insult, caves are actually fascinating places to study, explore, and even earn a Ph.D!

Caves serve as fascinating evolutionary laboratories and are home to a variety of species, many of which have converged on adaptations allowing them to thrive underground. From invertebrates to fish to salamanders, cave-obligate species have repeatedly lost vision/eyes, deactivated pigments, slowed metabolic rates, and evolved behaviors to survive in a nutrient poor environment where most organic material gets washed in from the surface! Many cave food webs are based on bat guano, thus highlighting the importance of bats to the persistence of many cave species. Additionally, cave species are often overlooked when it comes to conservation efforts. This can be a HUGE problem because cave species are imperiled when you combine habitat-specialization, high rates of endemism and low rates of dispersal with a suite of anthropogenic threats (think groundwater pollution or climate change).

Cave crayfish

Cave millipede

Much of my research involves the study of biogeography–I like discovering when and how species got to where they are. Cave systems seemed like an excellent ecosystem which has been relatively ignored in genetic studies. Furthermore, I was living only an hour from the beautiful Ozark Plateau, which is known as a biodiversity hotspot with many endemic species (including several cave species) but was lacking for studies testing biogeographic hypotheses which can be crucial for conservation efforts. The Ozarks are made from limestone karst, which is easily fragmentable rock and often dissolves in ways that produce amazing caves and subsequently their fauna. There are over 10,000 caves in the Ozark Plateau, many of which have not been well-studied to understand their biodiversity.

Gyrinophilus palleucus

In one of my studies, I looked at the Grotto Salamander (Eurycea spelaea) that is unique among salamanders. While there are only 12 described cave-obligate species of salamanders in the world almost are paedomorphic, which means they retain characteristics of larvae throughout their life (predominantly gills and a fully aquatic lifestyle, see picture of the Tennessee Cave Salamander (Gyrinophilus palleucus)). Typically, these salamanders will never leave the cave. However, the Grotto Salamander larvae (pictured) can inhabit surface streams and possess fully functional eyes. After several years as larvae they metamorphose into adults, losing their gills, pigments, and eyes, whereupon they leave the water and are free to climb about the cave walls.

 

Grotto Salamander larvae (Eurycea spelaea)

As a group, salamanders employ various life-history strategies, but none as unique as this. All grotto salamanders obligately metamorphose, indicating this an evolved strategy as opposed to something environmentally driven. Because of this unique life-history shift, my colleagues (Ron Bonett: University of Tulsa, Sarah Emel: UMass – Amherst, and Danté Fenolio: San Antonio Zoo) were interested in testing colonization patterns of Grotto Salamanders across the Ozark Plateau. Grotto Salamanders occupy a much larger range than other cave salamanders (See #1 on the map below). Could this be due to the surface-dwelling larvae following drainage patterns? Or do the terrestrial adults disperse underground more readily that their fully aquatic relatives? SPOILER ALERT: It is actually hard to distinguish between the two causes, but using the DNA of these salamanders we find that the geologic history of the Ozarks and major changes in drainage basins of the regions combine to explain a majority of genetic variation.

How much genetic variation? Well we have discovered three highly divergent lineages of grotto salamanders dating back 10–15 million years. While these three groups have not changed noticeably in their morphological features (so far as we can tell yet), they are considerably more different genetically than many other species of salamanders are to one another. Therefore, my colleagues and I have “re-elevated” each lineage to species status based on strongly supported genetic differences and geographical separation (see lower map). This phenomenon–where multiple species are unknowingly classified as a single species–is known as “cryptic speciation”. This has turned out to be quite common in cave species. Partially due to their lack of study. Hopefully our efforts here will help conservation agencies (in Oklahoma, Arkansas, Missouri, and Kansas) better manage these lineages across their range.

Eurycea braggi

Eurycea nerea

For more info on my Grotto Salamander work, feel free to read: Phillips, J.G., Fenolio, D.B., Emel, S.L., Bonett, R.M., 2017. Hydrologic and geologic history of the Ozark Plateau drive phylogenomic patterns in a cave-obligate salamander. J. Biogeogr. 44, 2463–2474.

This work was done as part of my Ph.D. at the University of Tulsa in Oklahoma. Currently I am a postdoc at MSU with BEACON, EEBB, and the Department of Integrative Biology where I study evolution in Stickleback fish! Hopefully I will have another blog post down the line as my work here progresses.

 

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NCAT Research Excellence Award

We are very excited to congratulate Dr. Joe Graves and the entire BEACON team at NCAT for receiving this year’s Research Excellence Award for Interdisciplinary Team. Every spring, NCAT celebrates outstanding accomplishments and efforts of faculty innovators, mentors and dynamic leaders with a Celebration of Faculty Excellence in Research and Teaching Banquet. The Interdisciplinary Team award honors research teams that break down the traditional boundaries of academic disciplines.

Back row (L—R) Keara Coffield (G), Dr. Misty Thomas, Dr. Joe Graves, Kimberly Hunter (UG), Dr. Jude Akamu Ewunkem, Sada Boyd (G). Front Row: Danielle Williams (G), Dr. Jessica Han, Anuolowapo Odelade (G), Adero Campbell (G); Janelle Robinson (G).

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Art and Science, Science and Art: Science outreach to young artists

This post is by MSU grad student Cybil Nicole “Nikki” Cavalieri

Figure 1: Leonardo da Vinci Antonym of a women; Ernst Haeckel Thalamorpha Plate; Young REACH artist with a Terror Bird

“I am not good at science, I am more artistic.”

“I have decided to drop biology, I am changing my degree to packaging I want to work in a field that lets me be creative.”

“I can’t draw the shape of this skull I am not an artist.”

These are things undergraduate students at Michigan State have told me. Science and art have not always existed in the polarized state we think they do. They have always been connected. In fact, the similarities between artists and scientists far outweigh the stereotypical differences. Neither fear the unknown. They welcome it.

Art communicates scientific research. Art is how we visualize our data. Every scatterplot, phylogeny, and manuscript are art. They might not be judged on their beauty, emotion and uniqueness, but they are still art. Collaborations between artists and scientists can be fruitful. Artists can serve as partners in the communication of scientific research. They can help us visualize data in new ways. They can help us make our results easier to understand and present them more compellingly. Also, they can help us reach a larger and different audience with our scientific message. Not only can art help visualize data, art is data. Researches have examined paintings from the Tate and National Gallery in London (1500 – 2000 BCE) of sunsets as a proxy for information about the aerosol optical depth after major volcanic eruptions. Historically science has produced the materials (pigments, canvas, photographic emulsion etc.) and methods of art. Modern collaborations are more than just better paint. Modern artists use materials from the realm of science such as bacteria, robotics, and computer languages to express their visions. Scientists and artists have even teamed up to explore how art affects the human brain.

Figure 2a: Nikki Cavalieri shows artists pygmy hippo skull.

Figure 2b: Nikki Cavalieri explains the evolution of morphology in primates.

 

 

 

 

 

 

 

 

Figure 3: Kasey Pham botanical artist drawing squash.

In recent years there has been a push to change STEM (Science Teaching Education and Mathematics) to STEAM (STEAM plus an A for art) to ensure that creativity is not left out of education. A group of MSU scientists have been spending one afternoon each month communing with teen artists at a fantastic local (Lansing) community arts center called REACH!. Our goal is to connect MSU students and staff who seek to bridge science and art with junior high and high school artists. Through activities at REACH, we aim to link art and science in as many ways as possible. In one of our earlier visits, I brought museum specimens (Figure 2) for the REACH kids to sketch, emphasizing the link between biological form and function. Later, I helped them develop chimeras incorporating morphologies of plants and animals, endowed with adaptations befitting a randomly chosen (‘wheel of fortune’ style) environment. During another visit, Kasey Pham (Figure 3) brought a live chameleon and tarantula for students to draw. This gave them a chance to focus on the dynamics of animal movement, and the intricacies of the integument – how light catches hairs, scales, and colors. As a talented artist who is also a plant scientist, Kasey spent one afternoon teaching teens about the chemistry of henna tattooing and then left the kids (and us) with favorite animals stained on our arms.

Figure 4: Young artists examines a human skull, it is important to note there was a concurrent costume party.

Figure 5: Kasey Pham shares her artist notebook with students.

Figure 6: Artist drawing goliath frog, pygmy hippo and Dinocrocuta skull

 

Figure 7: Kasey Pham gives Eben Gering a henna tattoo.

Figure 8: Artist showing off their sweet henna tattoos.

Figure 9: Artist showing off their sweet henna tattoos.

The world is a much poorer place when we separate things that should be together. It is important that developing artists and scientists see that science and art are not opposed. Through this program and programs like it hopefully future students will understand it is not art or science it is art and science.

 

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Evolution is the New Deep Learning

This is a repost of a blog post by Risto Miikkulainen, Vice President Research; Professor of Computer Science at the University of Texas at Austin

At Sentient, we have an entire team dedicated to research and experimentation in AI. Over the past few years, the team has focused on developing new methods in Evolutionary Computation (EC), i.e. designing artificial neural network architectures, building commercial applications, and solving challenging computational problems using methods inspired by natural evolution. This research builds upon more than 25 years of research at UT Austin and other academic institutions, and coincides with related efforts recently at OpenAI, DeepMind, Google Brain, and Uber. There is significant momentum building in this area; indeed, we believe evolutionary computation may well be the next big thing in AI technology.

Like Deep Learning (DL), EC was introduced decades ago, and it is currently experiencing a similar boost from the available big compute and big data. However, it addresses a distinctly different need: Whereas DL focuses on modeling what we already know, EC focuses on creating new knowledge. In that sense, it is the next step up from DL: Whereas DL makes it possible to recognize new instances of objects and speech within familiar categories, EC makes it possible to discover entirely new objects and behaviors—those that maximize a given objective. Thus, EC makes a host of new applications possible: designing more effective behaviors for robots and virtual agents; creating more effective and cheaper health interventions, growth recipes for agriculture, and mechanical and biological processes.

Today, Sentient released five papers and a web portal reporting significant progress in taking this step, focusing on three areas: (1) DL architectures are evolved to exceed state of the art in three standard machine learning benchmarks; (2) techniques are developed for increasing performance and reliability of evolution in real-world applications; and (3) evolutionary problem solving is demonstrated on very hard computational problems.

This post focuses on the first of these areas, i.e. optimization of DL architectures with EC.

Sentient Reveals Breakthrough Research in Neuroevolution

Much of the power of deep learning comes from the size and complexity of the networks. With neuroevolution, the DL architecture (i.e. network topology, modules, and hyperparameters) can be optimized beyond human ability. The three demos that we will cover in this article are Omni Draw, Celeb Match, and the Music Maker (Language Modeling). In all three examples, Sentient successfully surpassed the state-of-the-art DL benchmark using neuroevolution.

Music Maker (Language Modeling)

In the Language Modeling domain, the system is trained to predict the next word in a “language corpus”, i.e. a large collection of text such as several years of the Wall Street Journal. After the network has made its prediction, this input can be looped back into its input, and the network can generate an entire sequence of words. Interestingly, the same technique applies equally well to musical sequences, where it makes for a fun demo. The user inputs a few initial notes, and the system improvises an entire melody based on that starting point. By means of neuroevolution, Sentient optimized the design of the gated recurrent (Long Short-Term Memory or LSTM) nodes (i.e. the network’s “memory” structure) to make the model more accurate in predicting the next note.

In the language modeling domain (i.e. predicting the next word in a language corpus called Penn Tree Bank), the benchmark is defined by Perplexity Points, a measurement of how well a probabilistic model can predict real samples. The lower the number the better, as we want the model to be less “perplexed” when predicting the next word in a sequence. In this case, Sentient beat the standard LSTM structure by 10.8 Perplexity Points. Remarkably, although several human-designed LSTM variations have been proposed, they have not improved performance much—LSTM structure was essentially unchanged for 25 years. Our neuroevolution experiments showed that it can, as a matter of fact, be improved significantly by adding more complexity, i.e. memory cells and more nonlinear, parallel pathways.

Why does this breakthrough matter? Language is a powerful and complex construct of human intelligence. Language modeling, i.e. predicting the next word in a text, is a benchmark that measures how well machine learning methods can learn language structure. It is therefore a surrogate for building natural language processing systems that includes speech and language interfaces, machine translation (such as Google Translate), and even medical data such as DNA sequences and heart rate diagnosis. The better we can do in the language modeling benchmark, the better language processing systems we can build, using the same technology.

Omni Draw

Omniglot is a handwritten character recognition benchmark on recognizing characters in 50 different alphabets, including real languages like Cyrillic (written Russian), Japanese, and Hebrew, to artificial languages such as Tengwar (the written language in Lord of the Rings).