Slides for Bioinformatics Lab 2022

1. Bioinformatics Lab
MICROBIO 590B Bioinformatics Lab: Bacterial Genomics
Professor Kristen DeAngelis
UMass Amherst
Fall 2022
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2. Lecture Learning Goals
• Describe some instances where genomics has been used to better
understand ecosystems and ecosystem processes.
• Explain how ecology and evolution can both act as forces of change of
microbes due to climate change.
• List some of the related projects going on in the DeAngelis lab that
are the basis for this Course-Based Undergraduate Research
Experience (CURE) course
• Review the contents of the syllabus, and and summarize the major
activities and assessments of this course.
• Set up the key accounts and access required for our class activities.
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3. Example questions we might have:
• How will drought affect water availability?
• How will climate warming affect terrestrial
carbon storage?
… these can be answered using
bioinformatics and genomics!
How can genomics be used to better understand
ecosystems and ecosystem processes?
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Leung et al., mSystems (2020)

4. Relman, DA.
“Microbial Genomics
and Infectious
Diseases” , NEJM 2011
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5. Genome-enabled disease epidemiology
• 32 kbp genome, ssRNA (+)
sense
• One of the largest known
RNA virus genomes
• Able to mutate and change
at a high rate
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https://nextstrain.org/ncov/global
Global SARS-CoV-2 as of 9 Mar 2021

6. Genome-enabled disease epidemiology
• 32 kbp genome, ssRNA (+)
sense
• One of the largest known
RNA virus genomes
• Able to mutate and change
at a high rate
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https://nextstrain.org/ncov/global
Global SARS-CoV-2 as of 11 Jun 2021

7. Genome-enabled disease epidemiology
• 32 kbp genome, ssRNA (+)
sense
• One of the largest known
RNA virus genomes
• Able to mutate and change
at a high rate
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https://nextstrain.org/ncov/global
Global SARS-CoV-2 as of 28 Aug 2021

8. Simonsen et al 2019
Genomics offer insights into microbial ecology
• How does climate (rainfall and
temperature) shape microbial
populations across the landscape?
• Isolates of Rhizobia from Acacia tree
soil were genome sequenced
• Climate-associated genomic clusters
suggested that soil symbionts
showed ecological specialization
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9. Genomics can expand known diversity
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10. Soil microbes adapt to
climate warming
Kristen M. DeAngelis, PhD
University of Massachusetts Amherst
ISME18 Lausanne, 19 August 2022
deangelis@microbio.umass.edu, @kristenobacter
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11. We are now in the Anthropocene
Climate.NASA.gov

12. Soil microbes
mediate carbon flux between
the land and
the atmosphere.
Climate change disrupts the
global carbon cycle

13. How does climate change
disrupt soil microbial
carbon cycling?
Acclimation versus
adaptation
• Fast vs slow
• Temporary vs permanent
• Ecology vs evolution
Chapman T&F 2008
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14. Adaptation is heritable, & irreversible
Addition and
loss of
species
Changes in community
composition and structure
Genetic changes
(adaptation)
Generations of long-term warming
Fast response Slower response
M. Choudoir, adapted from Bang et al. (2018)
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15. Harvard Forest Warming Experiments
36m2, 6 replicates
Barre Woods: 18
years
900m2, 1 replicate
Prospect Hill: 30 years
SWaN plots: 15 years
9m2, 6
replicates

17. How are bacteria adapting to warming?

18. Culture collection of
soil bacteria
• >800 individuals
• 8 phyla in over 42 families
• Tree shows 283 taxa
• Blue bars are bacteria isolated
from control plots
• Red bars are bacteria isolated
from heated plots
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19. Δ(Htd
–
Ctl)
Soil
CO
2
flux
(g
CO
2
-C
m
-2
y
-1
)
HYPOTHESES:
• Because of accelerated soil organic matter loss with warming, bacteria are
better at carbohydrate degradation.
• Warming is associated with less water retention in soil, so bacteria exposed
to chronic warming show drought tolerance.
• Bacteria exposed to chronic warming show genomic signals of adaptation.
How are bacteria adapting to warming?
Diversity (PD)
Carbon
Use
Efficiency
(%)
30%
WHC
60%
WHC
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Melillo et al., 2017; Domeignoz-Horta et al., 2020

20. Warming is associated with…
more decomposition of carbohydrates
Warming is associated
with increased
potential to degrade
• Cellulose
• Xylan
• Not chitin
Pold et al., 2017

21. Warming is associated with…
increased drought tolerance
A. Narayanan, in prep
**
*
Model soils =
• Minerals (Sand, Clay)
• Simple nutrients
• Actinobacteria

22. Collect soil samples from control
and heated plots
Targeted enrichment of
microbial taxa by
high-throughput screening
Whole genome sequencing
Using MinION only or
combined with Ilumina
Mallory
Choudoir
What are the genomic markers of
bacterial adaptation to climate warming?
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23. • Whole genome phylogeny using
concatenated ribosomal proteins
• 78 soil bacteria isolated from HF
long-term warming experiment
• 3 Phyla (Actinobacteria,
Alphaproteobacteria,
Betaproteobacteria)
• 5 Genus (Kitasatospora,
Streptomyces, Bradyrhizobium,
Rhizobium, Ralstonia)
Comparative genomics

24. Pangenome analysis (n=78)

25. Codon usage bias increases with warming
M. Choudoir, in prep
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26. Codon usage bias increases with warming
M. Choudoir, in prep
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27. • Soil bacteria have acquired new traits in response to
long-term climate warming
•Soil bacteria show genomic signatures of adaptation, an
irreversible and heritable change
• Understanding microbial ecology and evolution of
climate change will improve carbon models.
Conclusions

28. Acknowledgements
• Mallory Choudoir, Achala Narayanan, Ashely
Eng, Luiz Domeignoz-Horta, Grace Pold,
Melissa Shinfuku (UMass)
• Ravi Ranjan, David Follette (IALS Core)
• Maureen Morrow (SUNY New Paltz)
• Jerry Melillo (MBL)
• Serita Frey, Mel Knorr (UNH)

29. MICROBIO 590B
• About me
• Course information
• Growth mindset
• Course goals
• Structure of the course
• Course activities
• Grade basis
• Tools
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30. Instructor information
Professor Kristen DeAngelis
Department of Microbiology
Member of OEB and PB graduate programs
Lab & Office: 4th floor LSL
Email: deangelis@microbio.umass.edu
Class meetings: M & W 9:05am to 11:00am
Office hours: M & W 8:30 to 9:05, also by
appointment
https://kristendeangelis.net
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31. About me
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32. • We have a large bacterial culture collection, with
opportunities to ask about adaptive traits to long-
term warming and drying.
• We have many bacterial genomes for new or poorly
characterized groups of microbes, with
opportunities to study more about their physiology.
• We are integrating bacterial adaptive traits into
trait-based models, such as MIMICS, with
opportunities to ask, how does bacterial adaptation
affect feedbacks to climate?
• We’ll be running our local adaptation experiment
next summer using the iChips, with opportunities to
help measure warming effects on fitness.
• We are broadly interested in how microbes indicate
soil health across systems (global, forest, coastal)
using meta-analyses, with opportunities to
contribute to this work.
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33. Course Information
• WHEN
• M & W 9:05 am to 11:00 am
• Student hours M & W 8:30 - 9:05 am, also by appointment
• WHERE
• 212 Morrill III
• We will all use Zoom for screen sharing, but attendance in person is required
• WHAT DO YOU NEED
• You will need a computer for this class with permissions to install new
software. If this presents a hardship, please let me know before class begins.
• Some microbiology: MICROBIO 310 or 311, or equivalent.
• A growth mindset !
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34. Growth mindset
• aka “grit”, “persistence”
• Intelligence is not fixed!
• “Individuals who believe their talents
can be developed (through hard work,
good strategies, and input from others)
have a growth mindset. They tend to
achieve more than those with a more
fixed mindset (those who believe their
talents are innate gifts). This is because
they worry less about looking smart
and they put more energy into
learning.”
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Blackwell, et al. Child development (2007)
Hochanadel, Aaron, & Dora Finamore. Journal Int. Ed. Res. (2015)
Dweck, Carol Education Week 35.5 (2015); Harvard Business Review (2016)
https://hbr.org/2016/01/what-having-a-growth-mindset-actually-means

35. In Class
• At the beginning of class
• Log on to Zoom, mute yourself, and turn off your volume
• Navigate to the lab manual that we’re working on
• The Lab Manual is also your Lab Notebook
• There are 4 parts, and we will work in order
• Click on the lab manual link in Moodle to download a personal copy into your
google drive, and use this to take notes
• During class
• There will be a brief lecture & review of the reading: bring questions
• We will take some time to discuss papers, or review prior assessments
• We will work together through the Lab Manuals for a complete assembly,
classification, and annotation of an example genome (GP101)
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36. Activities in Class
• The first half of the semester (about) will be more ”cookbook,” where
you learn to code, become familiar with the tools we are using, and
get to know the major components for bioinformatics applied to
bacterial genomics
• Some time in October, you will be assigned the genome you will work
on for your Capstone Project
• These are new isolates from my research lab
• They have been sequenced using MinION, checked for quality, but not
analyzed
• Your will complete the same analyses we did for GP101 together, but this time
working independently and on your own
• You may work in pairs or small groups, but all assignments are to be
done individually
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37. Tools: MGHPCC
• Unity Cluster at Massachusetts Green
High Performance Computing Center
• MGHPCC.org
• Local cloud computing infrastructure
• Login from terminal using ssh
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38. Tools: KBase
• The Department of Energy Systems Biology
Knowledgebase (KBase) is a web-based knowledge
creation and discovery environment designed for
biologists and bioinformaticians.
• KBase enables users to analyze, share, and collaborate
using data and tools designed to help build
increasingly realistic models for biological function.
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39. Expectations
• You can expect from me
• Accommodations
• Fairness
• Encouragement: I am rooting for you! I want to you to learn. Help me
understand how to help you.
• What I expect from you
• Attendance and participation
• Communication
• Persistence and patience
• Academic honesty
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40. Questions?
• OnlineQuestions.org
• Event number 231562022
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41. What is the thing that is the most likely to be a
barrier to your success in this class?
“My lack of experience in programming”... “jargon”… “lack of
knowledge about coding”… “complete lack of coding experience”
• Good news! This class was designed for a microbiology student who
has little if any programming experience. Keep up with the work,
practice the programming using the tutorials, write down all your
questions, search for possible answers, and have patience.
“the only computer language I know is java” … “I struggle with
languages”
• If you have any experience with other computer languages, it will help
you with Linux. If you struggle with languages, don’t worry: this is
different. There’s a lot less memorization. Practice, practice, practice.
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42. What is the thing that is the most likely to be a
barrier to your success in this class?
“Not a lot of experience with genomics”... “don't have an amazing
understanding of molecular biology”
• Pay close attention to the readings from last week and this, in
addition to the lecture. Also spend more time on the microbiology
textbook. This is the absolute minimum needed for this class.
“not sure how much computer science background one needs from the
start to be successful in this course”
• Pre-requisites: MICROBIO 310 or MICROBIO 311 with a grade of C or
higher for Microbiology majors, BIO 285 or BIOCHEM 285 for non-
majors, or equivalent.
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43. What is the thing that is the most likely to be a
barrier to your success in this class?
“Time management”
• Keep up with the assignments, and make plenty of time each week,
well before class, to do the work. Even if class ends early, you can stay
until 12:30 (a time you’ve already assigned to this class) to do your
work: take the quizzes, start your problem sets, work on your project,
& talk with me & your classmates about the work.
“Open-ended problems”
• There will be a gradual transition from guided programming to
independent work. For the most part, there are not open-ended
questions, but there will be a range of acceptable answers for many
questions.
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44. For next week
• Reading
• Snyder, Introduction (p. 1-12)
• Snyder, Chapter 1, Structural Features of Bacterial Genomes (p37-38), The
Bacterial Genome (p 50-51), and Molecular Biology Manipulations with DNA
(p. 53-64)
• Begin to work through one of the the unix tutorials
• Review Problem Set 1, which will be due at the end of next week
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