UNIT I UNITY DIVERSITY OF LIFE Baby Campbell

UNIT I – UNITY & DIVERSITY OF LIFE Baby Campbell ~ Ch 1, 17, 24, 25 Big Campbell ~ Ch 1, 19, 27, 28, 31

Biology is. . . The Study of Life!

I. “THE STUDY OF. . . “ – EXPERIMENTAL DESIGN Inquiry-based

I. EXPERIMENTAL DESIGN, cont • Setting up a Controlled Experiment o Clearly defined purpose o Valid hypothesis ØTestable statement or prediction—it must be falsifiable ØIf it’s wrong, then the experiment should reveal it ØDo not use “I think …”, “My hypothesis is …”, etc! ØOften written in “If …, then …” format but not a requirement. Avoid if possible.

I. EXPERIMENTAL DESIGN, cont • Setting up a Controlled Experiment o Control Group Ø Benchmark or standard for comparison Ø Allows you to know if what was changed in experimental group is responsible for effect Ø Positive Controls have an expected positive result—show that your test works Ø Negative Controls are expected to have no effect—gives you confidence that variable changed is responsible for effect observed o Experimental or Test Group(s) Ø Only one factor should be changed by the experimenter in each test Ø Independent (Manipulated) Variable Ø Dependent (Responding) Variable

I. EXPERIMENTAL DESIGN, cont o Important Considerations Ø Controlled variables (aka control variables, constants) must be monitored v Easy to confuse with controls! v. Control = “control group” v. Controlled variable = “constant” Ø Sample Size Ø Are the results statistically significant? Ø Potential sources of error Ø Repeatability

A student observed that wrapping thin, insulated wire several times around a nail and attaching the leads to a battery made the nail magnetic. The student hypothesized that increasing the number of wrappings around the nail increases the magnetic strength of the electromagnet. He devised an experiment to test the effects of the number of wrappings on the number of paperclips the nail can pick up. For comparison, he removed the battery from his electromagnet and observed that it did not pick up any paperclips. He also tested a permanent magnet to see if it could pick up paperclips. 34. ________________ Dependent variable 35. ________________ Independent variable 36. ________________ Constant (give one valid example) 37. ________________ Control group example 38. ________________ Control group example

Does Drug X improve student performance? • One group of students given fake pill (placebo) • Several groups given different doses of Drug X. • One group given a drug already known to increase performance. • All groups, after treatment, take a test and are scored. – What is the positive control? Negative control? – Experimental group(s)? – Controlled variables, Ind variable, dep variable?

I. EXPERIMENTAL DESIGN, cont o Tables Ø Format § Descriptive title § Each row a different independent variable § Each column a different dependent variable § Include units in labels § Derived units (e. g. averages, rates, etc. ) are put in new columns on the right

I. EXPERIMENTAL DESIGN, cont o Graphs Ø Format § Descriptive title § Key § Units must be evenly spaced (line break) and labeled § Use at least half of available space § Use a ruler!!! Ø Graphing Dependent and independent variables: Ø DRY MIX § Continuous Independent Variable (e. g. , time) → ______ Graph § Discrete Independent Variable → _________ Graph § Other kinds of data: § Part of a Whole → _________ Graph § Histogram _______ distribution—how often does this value or group of values occur in a data set?

I. EXPERIMENTAL DESIGN, cont o Graphs, cont § For Height Lab … v Mean v Median v Mode v Range v Histogram Ø

I. EXPERIMENTAL DESIGN, cont o Graphs, cont § Bar graph versus histogram • Bar graphs and line graphs look at the relationship between two variables (use DRY MIX) • Histograms look at the distribution of values for one variable

1. Factor changed by experimenter; designed to test hypothesis 2. Type of graph used to represent data when independent variable is continuous; for example, time 3. Set-up used as a benchmark, standard for comparison 4. Calculation used to represent spread, variability of data 5. Variable plotted on X-axis of line graph 6. Calculation used to determine precision, accuracy of data mean 7. Factor monitored in experimental design to minimize possibility of error, increase repeatability 8. Type of graph used to illustrate frequency, patterns of data

I. EXPERIMENTAL DESIGN, cont o Graphs, cont § For Height Lab … v Mean = v Median = v Mode = v Range = Ø Ø Normal Distribution?

Histogram vs. Density Distribution Curve

I. EXPERIMENTAL DESIGN, cont o Data Analysis Ø Null Hypothesis v“Statement of No Effect: v. States that any differences in data sets are due to random errors that cannot be eliminated in experimental design/protocol v. For example, § There are no significant differences between predicted and observed data. § There are no significant differences between control group data and test group data. Ø Alternate Hypothesis Ø Statistical Analysis – Supports or refutes null hypothesis: Ø Answers question, Can we refute the null hypothesis?

I. EXPERIMENTAL DESIGN, cont v Standard Deviation Ø Describes the spread of values in a sample; that is, data variability

Mass of Peaches in an Orchard Population size N Mean = 101. 2 g 1 st Sampling 2 nd Sampling Experiment/replicate 1 Sample size n = 10 Sample mean = 103. 7 g Experiment/replicate 2 Sample size n = 10 Sample mean = 100. 5 g

• Does your sample mean reflect the true mean of the population? • How can we tell if two samples came from the same or different populations?

I. EXPERIMENTAL DESIGN, cont v Standard Error of the Mean Ø Predicts the accuracy of the calculated sample mean to actual population mean (the “true” mean). Ø Technically, the SEM is calculated by taking several samples from a population and finding the standard deviation of the means of those samples. Ø We can estimate the SEM with one sample, however, using the above equation.

I. EXPERIMENTAL DESIGN, cont v Standard Error of the Mean Ø For large values of n (n=10 or more), ± 2 SEM is a 95% confidence interval Ø That means that there is a 95% chance that the true population mean lies within the error bars. Ø In order to reject the null hypothesis between two data sets, error bars cannot overlap.

I. EXPERIMENTAL DESIGN, cont Examine the data below showing two different experiments in which the heart rate of 10 different individuals was measured in beats/minute. • Calculate the standard deviation for each data set. Round to the nearest whole number. • Null Hypothesis: X barstudy A = 70 Study A Study B X barstudy B = 75 68 68 70 84 76 90 Sstudy A = 4 62 60 Sstudy B = 12 70 92 72 58 74 64 67 66 68 78 70 86

I. EXPERIMENTAL DESIGN, cont • Is there is a significant difference between the average heart beat/minutes in the two data sets? Construct a graph to illustrate. Study A Study B 68 68 70 84 76 90 62 60 70 92 72 58 74 64 67 66 68 78 70 86 Sstudy A = 4 SEMstudy A = 1 Sstudy B = 12 SEMstudy B = 4

I. EXPERIMENTAL DESIGN, cont X barstudy A = 70 SEMstudy A = 1 X barstudy B = 75 SEMstudy B = 4

I. EXPERIMENTAL DESIGN, cont • Conclusion o Evaluate hypothesis Ø Was it supported, refuted, or were results inconclusive? o Interpretation of Statistical Analysis Ø What does the SD, SEM tell you about your results, experimental design? o Assess experimental design Ø Was there only one independent variable? Ø Were sources of error minimized? Ø Controlled variables/constants Ø Repeatable? • Theory vs Hypothesis

II. UNITY OF LIFE • Characteristics of Life o All living things are made of ______. § Prokaryotic § Eukaryotic

II. UNITY OF LIFE, cont. • Characteristics of Life, cont o Living things obtain and use energy. o Living things respond to their environment. o Living things grow and develop. o Living things maintain homeostasis. o Living things are based on a universal genetic code. o Living things reproduce. o As a group, living things evolve.

II. UNITY OF LIFE, cont. • Four “BIG IDEAS” in AP Biology 1) The process of evolution drives the diversity and unity of life. 2) Biological systems utilize free energy and molecular building blocks to grow, to reproduce, and to maintain dynamic homeostasis. 3) Living systems store, retrieve, transmit, and respond to information essential to life processes. 4) Biological systems interact, and these systems and their interactions possess complex properties.

VIRUSES

III. CHALLENGING THE BOUNDARIES OF LIFE • Viruses. . . Living or Nonliving? Ø Discovery of Viruses § First isolated by Ivanowsky in 1890 s from infected tobacco leaves § Crystallized by Stanley in 1935 – proved viruses were not cells Ø Acellular Ø May be described as particle or virion Ø Not capable of carrying out life processes without a host cell Ø Parasites; use host cell’s resources to replicate

III. BOUNDARIES, cont • Viruses, cont Ø Structures found in all viruses: § Viral genome v. DNA or RNA. v. May be single-stranded or double-stranded § Protein coat v. Known as a capsid v. Made up of protein subunits called capsomeres.

III. BOUNDARIES, cont • Viruses, cont Ø Structures/adaptations that may be present: § Viral envelope v. Typically derived from host cell membrane o Exception is Herpes virus, synthesized from nuclear envelope of host cell v. Aid in attachment. Envelope glycoproteins bind to receptor molecules on host cell v. Most viruses that infect animals have envelope v. Can be described as an evolutionary trade-off § Tail – Found in some viruses to aid in attachment

III. BOUNDARIES, cont

III. BOUNDARIES, cont Ø Viral Replication

III. BOUNDARIES, cont • Viruses, cont. Ø Bacteriophage § Infects bacteria § Bacterial Defense Mechanisms v. Restriction Enzymes v. CRISPR/Cas 9 System v. Coexistence

III. BOUNDARIES, cont Bacteriophage Replication LYTIC CYCLE 1. Lytic Cycle – Results in death of host cell.

III. BOUNDARIES, cont – Bacteriophage Replication LYSOGENIC CYCLE

IV. BOUNDARIES, cont Human Viruses

III. BOUNDARIES, cont – Human Viruses • Enveloped Viruses vs Non-enveloped Viruses Ø No envelope Ø With envelope

III. BOUNDARIES, cont – Human Viruses • DNA vs RNA Viruses Ø DNA Viruses § Herpes Virus

III. BOUNDARIES, cont – Human Viruses • DNA vs RNA Viruses Ø RNA Viruses § HIV

III. BOUNDARIES, cont • Prions o o o “Proteinaceous Infectious Particles” Infectious proteins; lack nucleic acid Cause Mad Cow Disease, Creutzfeldt-Jakob Disease Very long incubation period No treatment

IV. DIVERSITY OF LIFE • Classification v Domain v Kingdom v Phylum v Class v Order v Family v Genus v Species

IV. DIVERSITY, cont Kingdom Domain Type of Cell Structures Nutrition Description Archaebacteria • • Cell wall not made of _______ or ______ “_______ bacteria”; require ______ conditions Eubacteria • • Cell wall made of ________ Mostly ______ Ubiquitous; _____; may be pathogenic Protista • • Mostly ____ May have cell wall, chloroplasts, flagella Auto or hetero “________”; very diverse “kingdom” Fungi • • Mostly ____ Cell wall made of ______; no _______! Strictly ______ (______) All non-motile; ________ Plantae • • Cell wall made of ______; all have chloroplasts Strictly ______ (______) All non-motile Animalia • • Never have ____________; chloroplasts Strictly ______ (______) All ______ during life cycle; most complex

V. PROKARYOTES

V. PROKARYOTES • Archaebacteria Ø Examples include methanogens, thermoacidophiles, halophiles

V. PROKARYOTES – EUBACTERIA • Eubacteria Ø Ubiquitous Ø May be pathogenic Ø Classification v. Shape § Cocci § Bacilli § Spirilla

V. PROKARYOTES – EUBACTERIA, cont v Gram Stain Reaction

V. PROKARYOTES – EUBACTERIA, cont • Cell Structure • Plasmids Ø

V. PROKARYOTES – EUBACTERIA, cont Time (hours) Number of Bacterial Cells 0 1 1 8 2 64 3 512 4 4096 5 32 768 6 262 144 7 2 097 152 8 16 777 216 9 134 217 728 10 1 073 741 824 11 8 589 934 592 12 68 719 476 736 • Binary Fission Ø

V. PROKARYOTES – EUBACTERIA, cont • Adaptations Ø Capsule § Adherence § Protection § Associated with virulence Ø Pili § Conjugation Ø Endospore § Bacterial hibernation Ø Motility

V. PROKARYOTES – EUBACTERIA, cont • Adaptations, cont Ø Quorum Sensing/Biofilms § Fairly recent discovery § Bacteria exchange chemical communication signals § Multicellularity? ? ?

V. PROKARYOTES – EUBACTERIA, cont Ø “Sexual Reproduction” § Transformation § Transduction § Conjugation

EUKARYOTES

VI. “KINGDOM PROTISTA” • • Very diverse All _________ Mostly _________ Grouped according to nutrition requirements Ø Animal-like § Ingestive § Protozoans/Zooplankton § Include human pathogens Ø Plant-like § Photosynthetic § Algae, kelp, seaweed § Very important aquatic producers; phytoplankton Ø Fungus-like § Absorptive § Slime Molds

VI. PROTISTS, cont Protist Phylogeny. . . For now!

VII. KINGDOM FUNGI • Absorptive heterotrophs; release exoenzymes Ø Decomposers Ø Parasites Ø Mutualistic symbionts (lichens) • Primarily reproduce asexually • Classified according to reproductive structures • Include mushrooms, bracket fungi, puffballs, molds • Yeast Ø Unicellular Ø Reproduce asexually; budding Ø May be pathogenic

VIII. KINGDOM PLANTAE

IX. KINGDOM ANIMALIA