LABORATORY
MANUAL
BIOLOGY
317
ENDOCRINOLOGY
Fall
2016
Rooms:
W-3-066 & W-3-068
Th
9:30-12:30
NAME:
___________________________________
Dr. Kenneth L. Campbell, Professor
(Office
Hours W 11:00-1:00 or by appointment, 617-287-6676, ISC - 5720)
Kazi Islam, TA
(KaziNazrul.Islam001@umb.edu;
Office Hours, by appointment)
Matthew
W Howard, Preparator, W-2-034
Table of Contents
|
Aims and Objectives |
|
Imperatives |
|
Schedule |
|
Grading |
|
Data Analyses |
|
General Methods of Approach to
Unknowns |
|
Hormone-Receptor Binding, Immunoassays,
Hormone Dose-Response |
Aims and Objectives
The laboratory is meant to reinforce and
augment the materials presented in the lecture portion of this course.
Hopefully it will illustrate a number of important concepts and experimental
approaches in endocrinology, e.g., chemical and biochemical
characterization of regulatory molecules, dose-response, bioassay, immunoassay,
mechanism of hormone action, chemical and physical interruption of feedback
cycles, multiple levels of control exerted in the endocrine system, and
exposure to modern proteomics. In a practical sense, this laboratory will give
the participants experience in several chemical and biochemical methods, as
well as opportunities for handling small laboratory animals, techniques useful
in other physiology laboratories as well as in clinical or endocrine research
laboratories.
This laboratory will involve solution
of an unknown along with conduct of several experiments that are purposely not
defined in detail – students will finalize experimental design. The unknown is
meant as a multi-dimensional puzzle, perhaps more interesting than group
exercises. Paperwork is minimal and emphasis in evaluations will be placed on
experimental design, research in endocrine literature, and deductive thinking.
Many elements of the lecture and
laboratory for this course are at http://kcampbell.bio.umb.edu
so that students may access or refer to them whenever it is convenient. This
site includes copies of syllabi, lecture notes and illustrations, locations of
other web sites of potential interest, and an e-mail address for the course
instructor. This lab is always an "experiment" in educational
innovation. Hopefully the web site will prove useful to you and make your
life a bit easier as you take this course. Let us know what you find useful,
what works, what doesn't work, and what needs to be added; your help and
cooperation are appreciated.
We use a variation on other
laboratories you may have encountered that should be helpful to all of us.
Specifically, the major laboratory report for the term, covering efforts linked
to proteomic work will arise from a single study, will be subjected to
"peer" review prior to being rewritten and submitted to the course
instructors. Each student will write up the laboratory report, as they normally
would for submission to the instructor, by the first deadline date in the
syllabus. Three copies of these reports will be made and distributed to three
other students in the lab. The choice of reviewers will be made by the
instructor who will keep a list of reviewers. Each student will read and make
anonymous editorial comments on three lab reports over the course of two weeks.
These marked-up, edited, copies of the reports will be turned back to the
instructor and then given back to the student who wrote the report. That student
will then rewrite the report before submission to the instructor at the time of
the second deadline for that report. The edited initial
copies and the final draft will be turned in at the time of report
submission. Grading will include an
evaluation of both the report and the editorial work done by each student. It is hoped this exercise will assist students in honing
their written presentation skills along with providing a "real-world"
experience in how reports and scientific writings are normally generated.
I will state at the outset that
experiments can fail completely or in part. Such failure is something normally
encountered in the course of research, particularly if the paradigm or
hypothesis upon which a particular set of experiments is based has not been
repeatedly challenged by experiment. The other main reason for failure is,
however, more controllable. That is, the exercise of care in the conduct of the
experiment, the collection of the data, and the evaluation of that data. I have
too often observed investigators collecting notebook after notebook of data
which proves to be useless because care was not exercised in its collection and
organization: standards were not used to calibrate measurements; positive and
negative control samples were not tested along with the test samples;
instruments were used incorrectly; dates and/or concentrations were not
included in solution labels; time-of-day was not noted when blood samples were
taken; deviations from written protocols were used but not recorded. Such sins
of omission make research more difficult and expensive than it needs to be.
Please do not be guilty of such errors during this course.
In this course I also strive to expose
you to the research process including independent thinking and evaluation of
published material as well as written exposition of your own results. You will be asked to build on information you should
have encountered and acquired in past biology, chemistry, and mathematics
courses. You will be asked to use, manipulate, and calculate with
standard scientific units and notations during and outside the lab. This
is material that should have been mastered by this time in your training.
Do not assume everything will be provided as a simple recipe or set protocol;
you will be asked to decide on your own or with the help of your peers what the
order of some work should be, when things should happen, where to find
information, how to make up solutions, what experimental parameters should be
tested, and what experimental design should be used. In addition to trying to get people to
become more self-reliant and confident in their own knowledge, observational,
and intellectual abilities, I hope to make people going through this class
begin to ask questions about dogma presented in the literature as fact. And I
hope to encourage people to suggest designs for the disproof of
"accepted" hypotheses, i.e., to go beyond questioning
authority toward redirecting authority and uncovering "truth."
IMPERATIVES
All students must demonstrate responsibility
for helping to keep the laboratory and ancillary rooms clean. The class is too
large to function otherwise. This means policing these areas for debris,
helping to keep equipment and animal caging clean (and any animals used
adequately fed and watered), and keeping benches and floors wiped up. We do not
have enough lab help to have all the housekeeping done by someone else.
Moreover, we are sharing this lab with several other classes this term. The
potential for biologically active chemicals like hormones or animal waste,
dander, etc. to cause serious
allergic problems, particularly in already sensitive individuals, is too great
to ignore given the number of people who come into or near the lab during the
course of a term. Chemical solutions must be handled with respect to avoid
endangering others; hormones are biologically active so small, unintentional
doses can cause undesired effects. Please be as helpful and cooperative as you
can. As part of grading is also based on participation, the instructor will
note repeated noncompliance with these imperatives. I would hate to decrease
someone's grade for acts of omission.
Cleanup in the lab will also be very
important this term since you may each be doing something different on any
given day. Labels on solutions and specific apparatus, e.g.,
slide boxes, should include: contents,
concentrations, date prepared, preparer's initials or name and intended use. Be careful to store materials appropriately,
as protein solutions or high dilutions of steroids, thyroid hormones, etc.,
are prone to ready degradation or denaturation; be liberal in the use of
refrigeration and careful in the use of freezers (biological materials are better preserved in the cold but
macromolecules are sheared during the freeze-thaw cycle when aqueous solutions
are frozen and reliquified). Again since we will be sharing the lab with
others, materials must be put away between uses and everything must be well
labeled.
With preparation and cooperation I am certain this will be an
enjoyable and instructive semester for all of us.
Best Wishes,
Kenneth L. Campbell
Note:
Both
sections of Endocrinology 317 Lab meet at the same time. Both sections meet jointly in W-3-066 before
each lab then occupy W-3-066 and W-3-068 during lab.
SCHEDULE
|
Laboratory Date |
Report/Summary Due |
Comments |
|
09/08 |
Roll calls,
Introduction of the TA, Location of the Lab Manual Introduction:
Materials, Grading, Reports, Library Resources, Journals, Other sources,
Schedule, Expectations, Description & Presentation of Data, Units, Math |
Do not skip this session if you want to keep a seat in
the lab! Sections are full & the
Add/Drop deadline is Tuesday, September 13 (before the next lab meeting). Introduction:
Distribution of Unknowns and course introduction/background review. |
|
09/15 |
Unknown Hormones I: Classifications, physical characterizations |
Unknown Hormones Approach: melting point, TLC (2% HOAc, 1:1 EtOAc:Hexane), and ultrafiltration (30k MW cutoff), simple qualitative end-point detection: UV absorbance or spectrophotometer. |
|
09/22 |
Unknown Hormones II |
Unknown Hormones: Characterization completed. |
|
09/29 |
Discussion of Unknowns; Set up for Immunoassay
labs; Introduction of Proteomics |
This is clarification for the first summary &
necessary background for the Immunoassay and Proteomics labs. |
|
10/06 |
Lab Summary I: Solution of
Unknowns Due. Immunoassays I: Noncompetitive Assay |
Immunoassays: Noncompetitive hCG/LH enzyme-linked immunosorbent assay (ELISA) to be run on unknown synthetic urine samples using test strips. Standard curves and controls will be run. |
|
10/13 |
Immunoassays II: Competitive Assay |
Immunoassays: Solid-phase competitive estrone-glucuronide (EG) enzyme immunoassays (EIA) to be run on the panel of unknown urines (as above) plus standard curves to evaluate assays. This will use home ovulation kit materials. Results will be collated to the hCG/LH assays. |
|
10/20 |
Proteomics of Hormone Fragments I This is the basis for the major lab report. |
Proteomics: Exploration using computer methods of the digestion of protein hormones by target cells, the generation of proteolytic peptide products, and the identification of known proteins that contain sequences that are identical or similar to such peptides. Students will explore an assigned protein hormone. The lab report on the proteomics labs will be peer reviewed and returned for rewriting based on peer comments. |
|
10/27 |
Solution of Unknown Urine
Panel Due. Proteomics of Hormone Fragments II This is the basis for the major lab report. |
Proteomics: Continuation of the proteomics experiment, discussion of results and their presentation, plus introduction to the next 2 labs. |
|
11/03 |
Hormone Control Circuits I |
Feedback Controls: treatment of mice with methimazole, thyroid powder, or nothing followed by calorimetric evaluation of basal metabolism; baseline information should be collected at the beginning of thyroid treatment and after the course of treatment; comparisons of basal metabolic rate (O2 consumed/g body weight/min) and/or thermal output (calories/g body weight/min) should be made between treatment groups and change over time of treatment (treatment response rate). |
|
11/10 |
Lab
Report: Proteomics of Hormone
Fragments. 3 Copies Due. Hormone Mechanism I |
Mechanism of Hormone Action: Oxytocin on mouse uterus contraction; add inhibitors, blockers, or 2nd message enhancers (e.g., dbcAMP, IBMX, PMA, indomethacin, okadaic acid) in simple +/-/0 designs to look at effects of modulating intracellular signaling. Choose the chemicals to be used, compute how to make up the solutions beginning with available stock materials, and make up chemical solutions. |
|
11/17 |
Anonymous
Peer Reviewer Comments Due. Hormone Mechanism II |
Mechanism of Hormone Action: Oxytocin on mouse
uterus contraction; add inhibitors, blockers, or 2nd message enhancers (e.g.,
dbcAMP, IBMX, PMA, indomethacin, okadaic acid) in simple +/-/0 designs to
look at effects of modulating intracellular signaling. Finish making up
stock solutions, run the experiment, and collect the data. |
|
11/24 |
Thanksgiving Day |
Holiday |
|
12/01 |
Hormone Control Circuits II |
Feedback Controls: Continue work on feedback and discuss questions from other labs. Peer Reviewer comments will be redistributed to the authors of the reports. |
|
12/08 |
Final Lab Exam. Lab Report: Proteomics of Hormone Fragments. Final Copy and Peer Reviewed Drafts Due. |
--- |
Grading
Laboratory is worth 30% of your
overall grade. Course work for lecture is worth 70%. (Keep in mind, however,
that effort expended in lab and on reports is often the best way to learn facts
and concepts covered in lecture; lab is synergistic with lecture. They
reinforce one another.)
A total of 1000 points is awarded in
lab:
|
Attendance & Participation |
100 points |
|
Summary I: Unknown Hormone (Decision Grid & Conclusions) |
100 points |
|
Solution of Unknown Urine Panel (Results & Conclusions) |
100 points |
|
Major Report |
200 points |
|
Summary II: Hormone Mechanism (Result Grid & Conclusion) |
100 points |
|
Peer Reviewer Comments |
150 points |
|
Lab exam |
250 points |
SOLUTION OF UNKNOWN URINE PANEL: Due early in the term, this puzzle solution is meant to force
students to apply the basic rules and concepts described for immunoassays and
assays generally and to stimulate students to apply those concepts to a typical
forensic or clinical diagnostic task involving distinguishing males from
females and females at different stages of their ovarian cycles using
biological fluids and hormones as markers.
LAB NOTES: Part of the process of doing good lab work is keeping good notes.
Good notes include clear definition of the purpose of each experiment or test
you conduct, including: a definition of what you are trying to rule in or out
as a possible unknown, for example; dates, initials, and page numbers on each
page; and a brief summary in writing of how the test or experiment came out. In
addition, the notebook should contain a list of the articles and materials you
are reading as references and/or copies of those materials. All this will be
useful and important when it comes to writing up your summaries and reports and
the habit should come in useful later. Further considerations of what
constitutes "Good Laboratory Practice," GLP, are covered at http://www.anachem.umu.se/cgi-bin/jumpstation.exe?GLP-GMP.
Because of the importance of such considerations in industrial and biomedical
arenas -- places where many students end up being employed -- students are
encouraged to begin to familiarize themselves with this major quality assurance
material.
LAB REPORT: 5% Format, 10% English, 10% Abstract,
10% Introduction, 10% Materials & Methods, 25% Results, 25% Discussion, 5%
References
The
format follows that in most scientific journals; they provide examples. The
following outline is suggested and can be downloaded here. All reports -- no exceptions -- must be typed or
computer generated as gaining computer literacy is a part of science education (and
life) today.
TITLE
by
Name
Date (of submission, not drafting)
in partial fulfillment of
Endocrinology Laboratory, Biology 317
Department of Biology,
[No page number on cover page, all
others at bottom center.]
Abstract
[The Abstract should be a single
paragraph of no more than 200 words containing: a statement of purpose or
question addressed; a brief description of methods used;
presentation of the seminal or central findings obtained; and a summary
or conclusion based on the question posed and the results obtained. It is
usually written after the rest of the report.]
Introduction
[The Introduction should include a
presentation of the purpose of the experiments or question posed as well
as a brief description of the background material providing the rationale
for the experiments. It should also include a statement of anticipated
results or alternative hypotheses being tested.]
Materials
and Methods
[Materials and Methods should concentrate
on deviations from the protocols given and definitions of the experimental
groups handled or measured by a given student.]
Results
[Results presents the data
collected, including pooled data, in a meaningful and coherent manner.
Raw data is not presented
without further analyses or comparisons. This section should include the
tables, charts, graphs, figures and computations used to organize the data
collected and to analyze it so that final conclusions could be reached.
All these elements should be sufficiently detailed to tell some
portion of the overall story when presented alone, in the absence of an
accompanying text, as in a visual presentation. Tables, charts and
graphs should all have titles. Tables and charts should
contain explanatory footnotes defining the meaning of any numbers presented.
Graphs should have explanatory legends and axes that are labeled and
scaled in a logical manner, don't start the y-axis at 1.37 simply because
the first data point falls there -- start at 0 and include units of
measurement on the scale. In the textual portion of this section include
highlights of what is to be found in the graphs, tables, etc., and try to
avoid making judgements about the data in this section. All graphical materials or figures must be
introduced by a brief statement indicating why they are being presented and
what the key observations are.]
Discussion
[In the Discussion evaluate the results obtained in light of those obtained elsewhere but, more important, in light of the question(s) posed or the hypotheses
being tested. Use your results to answer the
question then go on to address tangential issues and the needs for
improvements in the protocol. (Reports containing discussions that draw no
conclusions from data gathered, or that indicate an absence of any meaningful
attempt to relate questions posed in the experiments to the results obtained,
will be given as low a score as feasible. Effort counts.)]
References
[References should be presented in
a consistent format and should be given as they would be in an English
paper, e.g.,
SUMMARY: 50% Results, 50% Conclusions.
Summaries are shortened versions of
the reports. They are meant to help organize the data for use in full reports
and as a stimulus to analyze parts of what may be a much longer experiment. The
Question or Purpose is meant to substitute for the Abstract and Introduction of
the reports. It need not be detailed or go into depth as far as background is
concerned. It may contain figures that help organize concepts or help pose the
problem under investigation. The Results should include treated raw data,
transformations of data such as rates or percent of control, graphs, tables, or
charts that allow conclusions to be drawn, along with appropriate explanatory text indicating what is
contained in the graphics and why the graphics are presented. The Summary or Conclusion is simply a
statement of conclusions reached concerning the questions posed based on the
results obtained. It does not need to include the sorts of comparisons with
other data that are desirable in a longer report. References should also be
included in the Summary.
The Summaries will be shortened to a
maximum of two pages in 2016; for the hormone unknown, the urine panel
unknowns, and the mechanism of hormone action the summary will consist of a 1-2
sentence statement of the purpose of the experiment, a decision tree, a
computed results grid, a statement of conclusions (not summary) based on the
computed data, and a list of references cited in the report (not just read, but
cited). All written portions of the
Summary should be typed or computer generated.
Do not attempt to staple raw
data collections to a cover sheet and expect that to serve as a Summary; if you
don't wish to spend time generating the Summary, I refuse to spend much time
correcting it or trying to justify giving a grade for what is not present.
Peer
Reviewer Comments: These
are to be anonymous comments regarding the adequacy of your fellow student's
work. Similar comments will be made concerning your efforts. You are being
placed in the shoes of an instructor, or any other investigator, that might be
attempting to replicate the studies being reported. Reports must convey enough
information to allow such replication and/or to convince the reader that the
summaries and conclusions reached by the author are reasonable and logical
provided the results generated under the conditions described and given the
background under which the data are reported to have been collected and
evaluated. The big questions you must ask yourself as a reviewer are: 1) Is there a reasonable hypothesis stated that is
being tested? 2) Is the experiment, as described, reasonable for addressing
that hypothesis and is sufficient information provided that would allow the
experiments to be repeated? 3) Are the results presented in a clear and logical
manner that allows me to understand what information was generated and how it
might be interpreted? And, 4) do the results and discussion provided allow me
to reach the same conclusions regarding the original hypothesis that the author
reaches (this includes being able to find background material in the references
provided)?
Comments should address the written
document, not the author who wrote them. They can, and should identify both the
weak and the strong points of the presentations: change that, but keep this.
You are not assigning any numerical values to comments. These will be critiques
of written work, they are not personal criticisms of the author and should not
be interpreted as such. No one's work is perfect. Along with any good
approaches you found when doing critiques, use the written comments on your own
report to improve the report for final submission; that is the principle
document being graded. Grading of comments will focus on how these
appropriately attempt to improve other's work and how carefully and adequately
they identify both good and bad elements in that work.
LAB EXAM: 1/3 practicum, 2/3 concepts,
essay and data evaluation.
Data
Analyses
A common problem encountered by
students in this laboratory involves the critical evaluation and interpretation
of data, e.g., are two test groups, or two individuals, identical in
their responses or even meaningfully different? In biological systems such
questions are confounded by the tendency of each individual specimen to respond
slightly differently from every other specimen or even differently from itself
from one time to the next. Such variation must be kept in mind and expected
when you examine the data generated in these laboratories. Do not expect all
ovariectomized mice treated with estradiol to have uteri that weigh exactly the
same amount.
[Please note that some of
the equations below do not retain format well in going to HTML, they are best
obtained from a statistics text or other source book. KLC]
But are the two results seen really
different? The best way to examine such differences is to test them by the use
of elementary statistics. For a group of 4 similarly treated animals the
arithmetical average of any observed variable is the mean for that variable, m
= x = [∑i=1-4(xi)]/N, where ∑i=1-4 means
sum of i = 1 to 4, N is the number of observations, here N = 4.
The mean is attended by a degree of
uncertainty as to whether it is the "true" mean, µ, i.e., the
one that would be observed if every possible subject were treated the same way
and then observed. If the processes governing the observed variable allow
random variation in all directions, the variation is distributed
"normally" and the uncertainty is quantitatively represented by a
measure termed the standard deviation, s. This is calculated as the square
root, √, of the average of the squares of the differences between the
group mean and the observed values:
s = √{[∑i=1-4(xi - x)2]/N}.
If N is small (<20), N is replaced
by N - 1 in the equation to give a result more reflective of the true
dispersion (Actually the adjustment is required to correctly reflect the number
of "degrees of freedom" involved in the equation when differences
from a mean are involved.).
The standard deviation, s, actually
measures the width at the inflection points of the standard, normal,
bell-shaped, Gaussian, distribution theoretically associated with the observed
data. As such, 66.7% of all possible values of the observed mean should fall
between x - 1 s and x + 1 s, if the sample used to calculate x is
not systematically biased in some way. Moreover, 95+% of the
possible values of x should fall within x - 2 s and x + 2 s.
The utility of s becomes
obvious if there are several observations or measurements within a set that
seem "way off" for unexplained reasons. Such "outliers" can
be eliminated from means or comparisons by first generating x and s for
the other observations involved. If the outlier lies more than 2 s above
or below x you have a statistically meaningful reason to eliminate that
observation from further consideration in your dataset. (Caution: This
procedure cannot be applied repeatedly to the same group of results without
violating the statistical assumptions underlying the procedure.) Likewise, in
statistically testing whether two means are different or not you are
effectively generating an x and s for all the data lumped together and
then asking if the group mean's, x with a caret hat, for the various subgroups
differ from the overall mean or from each other by more than 2 s (or
some other chosen statistical distance), where s here is defined by the
overall dataset.
One of the easiest ways to visualize
comparisons among means is to draw line or bar graphs that have the means
indicated as points and the standard deviations for each point indicated as
lines or bars above and below these points. If variations around the means are
quite uniform in size, then, if the standard deviations for two means do not
overlap, there is probably a statistical difference between the means. The
larger the N's are for each mean the more likely this is to be true.
There is a mathematical test that can
be used in many cases to give an actual confidence level to the prediction of
whether two means are actually different (or similar). It is called Student's
t-test and generates a value for the difference between two means that can be
compared to a standard table, a t-table, computed for several levels of
probability or confidence and for several pairs of Ni values. If the
value calculated for t for the difference between the means of the two groups
exceeds the t value at, say, 0.05 then these group means have a 95% probability
of being statistically different from one another even if every possible
individual in each group was observed or measured. Computationally:
t = (x1 - x2)/[√(s12/N1
+ s22/N2)]
Note, however, that the t-test is
strictly appropriate only for the comparison of two groups that are independent
of one another. It should not be used to compare the same animals before and
after treatment, nor should a single control group be tested by this method
against more than one experimental group in a given experiment. These latter
"time series" and "multigroup" comparisons are better
handled by application of other statistical tools such as ANOVA, analysis of
variance, or Dunnett's multirange t-test. If time allows during our experiment
discussions later in the term we may be able to describe some of these tests.
They will not be fully expanded here; refer to a statistics text for more
details, e.g., http://www.richland.cc.il.us/james/lecture/m170/
or http://davidmlane.com/hyperstat/index.html.
If we have conducted an experiment and
suspect that two test groups differ, we want to discern whether the apparent
differences between the groups is a real phenomenon or simply due to random
variations in, for example, subject selection, measurements, or experimental
conditions. The approach to statistically testing for a difference is
based in logical argument. Because it is easier to disprove a statement
by finding a single exception to the statement or to show that contributing
factors may give rise to apparent differences, the usual starting, or null,
hypothesis, H0, put forward when group differences are suspected is
that the groups in question do not differ. That is, that the only
contributors to any apparent difference are from random, extraneous factors,
rather than that factor being evaluated. The alternative hypothesis, H1,
in this case, is then that they do differ because of the factor being
evaluated. If, using a statistical test, the groups are found to differ,
the experimental data allow rejection of the H0 hypothesis and
acceptance of the H1 alternative. Conversely, if the groups do not
differ, H0 cannot be rejected and the alternative H1 is
not supported. Note that, because the probability of failing to reject H0
when it is false is often larger than the probability of rejecting H0 when
it is true, we can normally be more certain that H1 is true if H0
is not than we can that H1 is not true if H0 appears to
be true. The inference structure is asymmetric, so conclusions are more
definitive when H0 is rejected than when it is accepted. This
means more experimental progress is made when null hypotheses are constructed
so that tests results allow their clear rejection. If a starting hypothesis
is rejected, we can design a new experiment to test a new hypothesis. If
the starting hypothesis is not rejected, we are forced to replicate or expand
the old test or move in another experimental direction. Note that in
biological systems we often have a mechanistic picture or model that allows the
construction of the hypothesis, H0. If we fail to reject H0
we know that, at least under the conditions studied, the model appears to work.
This is not terribly informative in that it may simply mean we chose the wrong
conditions to show where the model's faults lie. If we reject H0,
we know, however, that something in the model is wrong, though not necessarily
what. The idea of a good experiment is thus to allow the most specific test of
a model possible to allow individual elements of the model to be tested and
eliminated or supported.
Do
not then be surprised if a model propounded by
the instructor is rejected by the data you generate. Your task is to interpret
your data in a meaningful way in the context of the model put forward and then
to suggest an alternative model and/or experiment to test that model.
General Methods of Approach to Unknowns
The unknowns distributed to you in
this laboratory will, in the main, be highly purified materials with discrete chemical,
biochemical, immunological and biological properties. They will be provided as
dry powders in small numbered vials. You should make every effort to keep the
stock material dry and cool, preferably refrigerated. Use the material
sparingly. It is expensive. Do not be so sparing as to be incapable of
determining what you have, however! I will retain the coding key that links you
and the identity of your unknown. (And, if necessary, I can provide more
material if that is required to complete the laboratory.) Unknowns may be
duplicated; more than one person may receive the same hormonal unknown. The
hormones distributed are drawn from the following list:
Progesterone
Estradiol-17ß
Testosterone
Gibberellin
Cortisol (hydrocortisone)
Thyroxine
Insulin
Human chorionic gonadotropin
Epinephrine
Indoleacetic acid
Oxytocin
The solution of these unknowns will
involve several basic biochemical tests. Characterization of the class of
compound will involve migration on thin-layer chromatography, melting point
determination, molecular sizing with ultrafiltration, and spectral evaluation
using a UV-visible spectrophotometer. Further characterization could involve
acrylamide electrophoresis, chromatography on other thin-layer systems, binding
to serum binding proteins, displacement of radioactive ligands in binding
systems, inhibition of enzymes or metabolism by specific cells or bacteria, etc. Immunological characterization
usually implies generation of a labeled-ligand displacement curve in an RIA or
ELISA/EIMA that is parallel to that obtained with a pure known compound.
Alternatively, serum binding proteins or crude target-cell receptor proteins
could be substituted for the specific antisera in a competitive binding assay.
For proteins, binding of multiple epitope-specific antibodies is further proof
of identity as is binding of a specific band on a Western blot to an antiserum
of known specificity. Further proofs of identity come from characterization of
bioactivity in a living system. This may be done by using a known response in
an intact system, e.g., a specific growth response, or it may be
accomplished by demonstrating the capacity to replace an ablated organ known to
be the source of a given hormone. Ultimately, a quantitative version of this
bioassay system may give parallel responses to a graded series of dilutions of
the unknown and a supply of pure hormone. Lastly, if possible, some
characterization of the mechanism of action stimulated by a given hormone would
provide a definitive identification of the unknowns. This would involve
demonstration that the hormone produced a predicted response in target cells
either morphologically or biochemically. Often this is demonstrable using an
immunoassay for the generation of a specific second-messenger, or the
pharmacological blockade of a response by drugs with previously defined
targets.
Your first summary will be a report on
your solution of the identity of your unknown. It should briefly define your
line of thought and intermediate hypotheses regarding the possible identity of
the compound. I suspect the path will consist of a series of binary decisions
based on negative inference (ruling out the possible compounds that do not fit
the results you have gathered); this can be arranged in a table. The summary
should be no longer than 2 pages, including the decision grid and cited
references. I do suggest that one place
to start finding pertinent information is in the library among the biochemistry
books and journals or in similar online data sources (from reputable sites, not
health food promoters or chatrooms). Learn to use the available Science
Search Databases and various Web sources such as PubMed to help find out
about specific subjects such as the properties of a given hormone or the assay
systems that have been used to measure it. Some of the Other Resources links on
this Web site may be quite helpful here: Other Resources. And
keep good notes in the lab.
IMMUNOASSAYS
A key tool in the development and
conduct of modern endocrinology is the immunoassay. It is now used to measure both small
molecules such as steroids and large ones including proteins of many kinds
including hormones and even nucleic acids.
The competitive version of the assay involving one antibody and a
radioactively labeled version of the analyte (radioimmunoassay, RIA) that was
originally developed and described by Yallow and Bernstein for measurement of
insulin has given way to a broad spectrum of assay variants. Small analytes/molecules most often are
measured using assays very similar to the original RIA with the substitution of
a colored, fluorescent, enzyme-labeled, or particle-labeled version of the
analyte being used to compete with the analyte in the sample for binding to a
limiting amount of high-affinity antibody either suspended in solution and
subsequently precipitated by addition of a secondary anti-antibody preparation
or bound to a surface such as a plastic bead or plate. While large molecules can be measured in
competitive IAs, they are now most often measured in some variety of
non-competitive immunoassay or immunometric assay (IMA) where one antibody
directed against a part of the molecule surface is first immobilized in a
non-limiting amount onto a surface so it cannot move. Analyte containing solutions, either standard
controls or unknowns, are incubated with the immobilized antibody so the
analyte can bind. A second antibody that
is modified to make it visible or quantifiable, e.g., radiolabeled, enzyme labeled, particle labeled, fluorescently
tagged, etc., is then added in
non-limiting amount and allowed to bind to the analyte molecules present. If all the analyte molecules have been
adsorbed to the first immobilized antibody, the second antibody-conjugate will
form a “sandwich” in which the analyte is the limiting “cheese” in the
sandwich. A wash of the plate to remove
non-bound second-antibody conjugate then allows the detection and quantitation
of the amount of immobilized conjugate topping the “sandwich.” By inference, that only occurs when analyte
is present so that measure is an index of the amount of analyte present in the
sample. By running samples that contain
known masses of analyte in these assays in wells that are separate from, but
otherwise identical to, those used for unknown samples the analyst can generate
a standard curve for that analyte in that assay. Since the results for the standards describe
the universe of possible results for the same analyte run under the same
conditions in the same assay, the response for any unknown containing that same
analyte should fall on the same curve.
So long as we know what the volume and dilution of the original sample
was placed into the assay, we can ascertain what mass is found in unknown well and
what mass and concentration exists in the original unknown sample. This information can then be compared to
tables of published values to ascertain if the sample came from a subject with
normal or abnormal health, from a male or a female, from a young or old
subject, from a pregnant or non-pregnant subject, etc. Note that many of these
same questions arise in human medicine, veterinary medicine, environmental
research, forensics, basic biological research, pharmaceutical development, and
regulatory biology.
This laboratory will allow students to
run both non-competitive and competitive immunoassays and to solve a
biomedical/forensic puzzle while doing so.
The class will work in groups.
Each group will be issued a series of 8 tubes that have been synthesized
by the instructor with one or more of the three possible analytes that will be
measured. Each group will run two
different assays; the second one will monitor two analytes with its results
reflecting one or both of them. Each
assay will involve measurement of a set of control standards of known
concentration along with measurement of the analyte solution or several
dilutions of that solution. The results
for both the controls and the unknowns will be recorded for each assay. Then, using that information plus information
students can find in the library or on the Internet, each sample will be
labeled as to gender and possible physiological status (young, old; pregnant,
non-pregnant; phase of menstrual cycle, etc.).
The solution of the unknown grid constitutes the report for the
exercise.
Sample
& Standard Storage
Before starting the ovulation test
assays label a 9x12 deep-well storage block with your group name. Place 1000 uL = 1.0 mL of each of the
undiluted unknowns into one well of the first column of the block: so 1000 uL
of unknown S goes into block well A1, 1000 uL of unknown T goes into block well
B1, etc. Into the third column of your
group’s block put 1000 uL of each of the 5 pregnancy test standards (0, 3, 10,
30, 100 mIU hCG/mL), e.g., 1000 uL of 3 mIU/mL hCG goes into B3, 1000 uL of 30
mIU/mL hCG goes into D3, etc. Finally,
into the fifth column of your group’s block put 1000 uL of each of the 7
ovulation test standards: (10 ng EG & 10 mIU LH)/mL in A5; (50 ng EG &
10 mIU LH)/mL in B5; (50 ng EG & 50 mIU LH)/mL in C5; (50 ng EG & 150
mIU LH)/mL in D5; (150 ng EG & 10 mIU LH)/mL in E5; (150 ng EG & 50 mIU
LH)/mL in F5; (150 ng EG & 150 mIU LH)/mL in G5. Place a plastic seal over this block and set
it aside until testing the unknowns.
Note these same blocks could be used to dilute the samples prior to
testing if that were required.
TABLE
|
|
1 |
2 |
3 |
4 |
5 |
6 |
7 |
8 |
9 |
10 |
11 |
12 |
|
A |
US |
|
PS0 |
|
OS1 |
|
|
|
|
|
|
|
|
B |
UT |
|
PS3 |
|
OS2 |
|
|
|
|
|
|
|
|
C |
UU |
|
PS10 |
|
OS3 |
|
|
|
|
|
|
|
|
D |
UV |
|
PS30 |
|
OS4 |
|
|
|
|
|
|
|
|
E |
UW |
|
PS100 |
|
OS5 |
|
|
|
|
|
|
|
|
F |
UX |
|
|
|
OS6 |
|
|
|
|
|
|
|
|
G |
UY |
|
|
|
OS7 |
|
|
|
|
|
|
|
|
H |
UZ |
|
|
|
|
|
|
|
|
|
|
|
Notes:
PS# signifies the
pregnancy or hCG control standard number used in each well; hCG concentrations are
in mIU/mL. OS# signifies the ovulatory
or estrone-glucuronide, EG, and LH standard used in each well: (10 ng EG &
10 mIU LH)/mL in A5; (50 ng EG & 10 mIU LH)/mL in B5; (50 ng EG & 50
mIU LH)/mL in C5; (50 ng EG & 150 mIU LH)/mL in D5; (150 ng EG & 10 mIU
LH)/mL in E5; (150 ng EG & 50 mIU LH)/mL in F5; (150 ng EG & 150 mIU
LH)/mL in G5.
The standards for the assays will be
made up in advance and will be stored at the front desk. Keep the order and
orientation of the blocks as shown! If you
do not you will not be able to match the results of the assay to the standard
or sample that you used in each assay. L
Noncompetitive
LH Assay
A non-competitive assay for hCG and/or
LH will be run by using materials from home pregnancy test kits. For these the capture antibody is immobilized
on one of two strips marked on a paper test pad glued to a plastic strip. The reporting, enzyme-conjugated, antibody
and substrate are impregnated into a portion of the pad above the maximal fill
position for the urine. Control
standards are provided in a series of marked tubes. The protocol is as follows.
1)
Use a marking pen to label each of 26
strips and test tubes with numbers from 1 to 26 plus the letter of your group
(A,B,C,D,E,F, or G). Record the strip
numbers in one column in your notes with room to also record an estimate of the
results and to tape the finished strips onto the note page.
2)
To each of the first 5 tubes add 0.5
mL of one of the control standards.
Repeat this for tubes 6 to 10.
You should have two tubes containing samples of each of the 5 control
standards. To each of tubes 11 and 12
add 0.5 mL of unknown S. To each of
tubes 13 and 14 add 0.5 mL of unknown T.
Repeat for each unknown until you have liquid in all 26 tubes (1 & 6
= 0 mIU/mL hCG control, 2 & 7 = 3
mIU/mL hCG control, 3 & 8 = 10 mIU/mL hCG control, 4 & 9 =
30 mIU/mL hCG control, 5 & 10 = 100
mIU/mL hCG control; 11 & 12 = unknown S, 13 & 14 = unknown T, 15 &
16 = unknown U, 17 & 18 = unknown V, 19 & 20 = unknown W, 21 & 22 =
unknown X, 23 & 24 = unknown Y, 25 & 26 = unknown Z.
3)
Take the appropriately labeled test
strips and place them into the concordant tubes. Keep your fingers off the test
pads and make sure they are immersed in the liquid in the tubes to no higher
than the indicated maximal fill line.
4)
Incubate the strips in the tubes for
30 minutes. Be consistent for all the
strips on the timing. Try to take them
all off within a minute or two of each other at most.
5)
Remove the strips and evaluate the test
lines on the pads on each strip.
6)
Place the control sample pairs next to
one another (1 & 6, 2 & 7, etc.) and note the increase in color that
should be apparent on the test line as the concentration of hCG increases (note
that the antibodies used may also detect LH so you would get the same effect by
using a series of LH controls). The 0
control is a blank and should not generate a colored test line.
7)
Place the unknown sample pairs next to
one another and note if each pair of strips generates a similar result. Then compare the unknown test lines with the
controls and see which controls match or bracket the unknowns. Record your estimates of hCG (1 mIU hCG ~
0.1ng hCG ~ 0.1 ng LH ~ 1 mIU LH) concentration in the unknowns.
8)
Compare your estimates with the ranges
previously reported for males and females, young vs old, etc. See if the data allows you to classify the
unknowns.
Competitive
Assays for Estrone Glucuronide and Non-competitive Assay for LH
Estrogen levels during the normal
menstrual cycle are higher in females than the levels seen in males. During steroid metabolism and excretion many
steroids are oxidized and/or conjugated to sugars or other compounds to make
them more water soluble and more easily eliminated in urine. Estradiol-17β usually appears in urine
as one of several conjugates, the most common of which is
estrone-3-glucuronide. Estrogen levels
in reproductive age women who are not using chemical contraceptives follow a
pattern. They are low during active
menstruation and the very early part of the follicular phase of the cycle, rise
rapidly toward the mid-cycle and the time of ovulation, then fall back somewhat
only to rise to a generally lower but still significant broad peak during the
latter half, or luteal phase, of the cycle.
If pregnancy occurs the levels rise throughout pregnancy to very high
levels by the third trimester. For women
taking combination steroid contraceptives the estrogen levels in blood and
urine are quite measurable by many steroid assays. For those taking only progesterone mimics,
estrogen levels are generally low as they will be in women who have not gone
through puberty, have passed through menopause, are lactating, or have a
cessation in cycles for unknown causes.
The steroid patterns in males and females of most mammals exhibit
variations that follow the general patterns outlined above.
Since steroids are small molecules two
antibodies cannot bind simultaneously to individual steroid molecules. Their assays are normally done in a
competitive format with a limiting amount of steroid specific antibody being
allowed to bind to a mixture of the unlabeled analyte and a labeled or
conjugated form of the analyte. This
molecular version of musical chairs generates a signal from those conjugated
analyte molecules that end up bound to the antibody after any unbound analyte
or conjugate molecules have been washed away.
Since binding to unbound steroid analyte would preclude binding of the
conjugate, the signal strength is inversely proportional to the amount of unbound
analyte present. Thus, in a competitive
assay the assay signal strength declines with increasing unlabeled analyte
concentration. It does not increase as
in a non-competitive assay.
Home fertility testing sometimes uses
monitoring of estrogen metabolite levels as a means to track progression
through the mid- to late part of the follicular phase of the ovarian cycle, the
segment preceding the LH surge and ovulation near the middle of the normal
menstrual cycle. The tests incorporate a
limited amount of immobilized anti-estrogen and an enzyme or other labeled form
of estrogen-conjugate which competes with the estrogen-conjugate that is
present in the biological sample being tested.
As urine moves up the sampling stick it wets the deposit of labeled
estrogen-conjugate and the substrate for the enzyme used, these mix with the
sample and move up the strip to the zone where the anti-estrogen antibody is
immobilized. Once the antibody binding
sites are filled any remaining labeled conjugate, unlabeled analyte, and enzyme
substrate will move beyond the competition zone. This can be enhanced by putting a large
excess of anti-estrogen antibody in a second zone further away from the dipping
end of the sampling strip. The second
zone draws the unbound labeled tracer away from the competition zone and allows
verification that the enzyme in that conjugate is active, that the test is
working. By reading the color intensity
(or absorbance) of the competition zone using an LED lamp and a
wavelength-tuned diode the result of the competitive immunoassay can be
ascertained (we will be doing this visually without an electronic reader). Storing this information allows subsequent
results to be compared with the initial test.
This comparison allows upward or downward trends to be identified. In the test we will be using, a strong upward
trend for estrogen triggers a decision by the test to stop monitoring estrogen
and, instead, to follow LH which is usually being tracked using a
non-competitive assay akin to the one used in the pregnancy tests we described
above. In a normal mammalian cycle a
rapid rise in estrogen above a minimal, species and individual specific,
baseline stimulates the rapid and repeated release of LHRH followed quickly by
the release of LH. When LH levels rise
to near a peak they trigger physiological, biochemical, and morphological
changes in the ovary and, soon thereafter (within 17 hours in the human) the
release of the mature oocyte, which is now ready for fertilization. The test monitor expresses rapid rises in
estrogen as flashing happy faces and near-peak and peak LH levels as stable
smiles. These are semi-quantitative
symbols of the underlying quantitative test results. (http://www.clearblueeasy.com/healthcare/clearblue-advanced-digital-ovulation-test.php)
Here each group will run an assay unit
for estrone glucuronide and LH. The
assays will be conducted per the manufacturer’s instructions except that we
will test a set of knows and unknowns as serial measurements with no more than
10-12 min per sample. The test strips
will be dipped into one of the standards or unknown samples in the labeled deep-well
blocks you set up earlier. Do the strips one at a
time as they must be read within a short period of time after sample exposure
and each reading will take about 5 – 8 min.
The strips can be read by eye
using similar strips that have been tested identically as comparison
references. After reading each sample,
record the result and prepare to read the next sample.
In each assay record in your notes the
order and placement of your samples in the plate wells. Follow the grid in Table 1 (above) so that
your readings can be compared to those of the standards.
The summary for this experiment will
involve filling out the assay response grid we provide and then drawing a
conclusion about the probable physiological states of the unknown sample
donors. The summary should be no longer
than 2 pages and should include references cited.
PROTEOMICS OF HORMONE FRAGMENTS
This lab exercise arises from some recent work in my
laboratory. While doing this study you
will be contributing to the existing research data on this topic. Basically, the idea is that many proteins
bind to their target cells, induce an initial signal inside the cells by
currently known transduction processes, and then are cleared from the cell
surface by the internalization and processing of the hormone-receptor complex. This processing often involves endocytosis of
the complexes with gradual movement of the endocytotic vesicles toward the cell
nucleus. The endocytotic vesicles may
have multiple possible fates as they may be routed: back toward the cell
surface where the receptor may be replaced into the cell membrane while the
hormone or its degraded forms may be released from the cell; toward fusion with
the Golgi Apparatus where the receptor and/or hormone may be
post-translationally reprocessed or reactivated so that after exocytosis from
the exocytotic granules generated by the Golgi the receptor may resume its
actions and/or the hormone may resume its actions or its fragments may be
released from the cell or be presented to adjacent cells as part of an immune
antigen-like complex on the surface of the target cell; to fusion with primary
lysosomes to form secondary lysosomes where the receptor and hormone are
proteolytically degraded into fragments that may eventually be released to the
exterior of the cell, may be stored as part of intracellular multi-vesicular
bodies, or may be released to the cell cytoplasm via one of several
mechanisms. Movement of the endocytic
vesicles toward the cell nucleus is accompanied by declines the interior pH in
these vesicles, starting from near 7.4 at or near the cell surface to as low as
4 in secondary lysosomes. The pH
declines mean that the activities of any proteases within the endosomes or
lysosomes varies so that proteases like cathepsin G are more active near the
cell surface while others like cathepsin D are most active in the late stages
of endosome/lysosome movement. If
protein hormones are not broken down to very small peptides or single amino
acids, the residual peptides may themselves possess hormonal or protein
modulatory actions. Our studies are
beginning to explore this possibility.
The steps are initially quite simple and will be followed in this
lab. 1) A protein hormone is chosen from
a list of the several hundred possible.
Each peptide chain is located in the existing national protein databases
(e.g., NCBI, UniProt, PDB, or SWISSProt) and the full length amino acid
sequence of the mature hormone is cut and pasted to a notebook. 2) This sequence is then explored for
protease resistant peptides by testing it in one of several published
proteolysis programs (often used to predict fragments when running mass
spectral analyses of proteins) such as PROSPER established and run by a group
at Monash University in Australia. We
will show you how to run this program as well as to how to check the results by
requesting results for only a single enzyme.
Any peptides greater than 8 amino acids long that survive exposure to
multiple proteases should be recorded, identified in the parent sequence, and used
in the next step of the analysis. 3) The resistant peptides, if any, are used
as the search sequences in classical protein BLAST searches of all existing
proteins in the national protein databases.
These are to be run using a local search paradigm along with the default
parameters we will describe in the lab.
Results for this step will produce a list of proteins that possess
linear segments that are either identical to the peptides being queried or are
similar in physicochemical properties as would occur by conservative amino acid
substitutions during protein evolution.
The longer the peptide being tested the more likely a meaningful match
will be found among those proteins showing high identity/similarity
values. The top 20 to 100 matches in
these searches should be recorded (use cut and paste methods to capture
results) and any groups of similar proteins noted (e.g., oxidases, transducers,
chaperones, etc.). If matches to known
peptide hormones are found these should especially be flagged as they demonstrate
the potential biological activity of the identified peptides. It will be most interesting if any patterns
of peptides or protein matches arise among the group of protein hormones
explored by this class.
Note that our research extends these results by looking not only
for linear sequence matches but also structural sequence matches which involve
three-dimensional modeling of the peptides involved and matching these to known
x-ray crystallographic or similar structures for known proteins. If such matches (or even linear ones) exist
for cytoplasmic or receptor proteins we would look for any protein partners
that the identified proteins interact with or bind to. If the identified motifs match the sites of
interactions for the identified protein and its complementary partner, it means
the protein hormone proteolytic peptide may be involved in modulation of the
action(s) of that pair of proteins, i.e., it may have a previously unknown
biological action. Bench tests of those
interactions can then be designed to test the strength or consequences of the
presence of the protein hormone-derived peptides.
This exercise expands our database in this area and may lead to
important new insights into how the endocrine system works!
HORMONE CONTROL CIRCUITS
This laboratory builds on a
demonstration of the role of thyroid hormone in altering oxygen consumption and
CO2 production in mice. It will start 4 weeks prior to the
final measurements of the experimental mice as this allows the time needed for
the treatments to demonstrate their effects.
Groups of mice will be treated with exogenous thyroxine or thyroid
powder which should move them toward a hyperthyroid state, with methimazole, a
goitrogen, which should move them toward hypothyroidism, or with nothing.
The animals will be monitored for weight gain and basal metabolic rate using a
computerized system that uses sensors to monitor both oxygen consumption
(oxygen electrode) and CO2 production (infrared sensor detects the
IR signal of the C=O bond). Changes with respect to basal metabolic rate
over time and type of treatment will be used to ascertain the degree of
alteration of the feedback control circuits generated by the pharmaceutical
agents. Details of the protocol and means of analyses will be arrived at
during laboratory discussions. Students should come prepared to discuss
what they have read concerning the control of the thyroid axis and its
modification during periods of hyperthyroid and hypothyroid status. Links
between thyroid status and general metabolic function should also be explored
prior to the lab.
MECHANISM OF ACTION EXPERIMENTS
The protocol for these experiments
will be discussed with the students in the lab. The actions of oxytocin
on contraction of mouse myometrial muscle will be examined. Students are
encouraged to search out information on this system and come prepared to share
that information. The idea will be to attempt to elucidate the pathway(s)
by which oxytocin is acting via pharmacological manipulations of intracellular
signaling pathways. Drugs known to stimulate or inhibit specific pathways
will be available. Decisions on designing the experiment will be made in
classroom discussions.
Note: this lab requires
students to make up solutions according to published bioactive
concentrations. Be prepared to calculate and physically work with molar
and/or weight/volume solutions. Be prepared to carry out dilutions from
liquids already prepared as well as to prepare solutions from dry raw
materials. Be ready to conduct serial dilutions. Think about how
masses are measured and transferred, how volumes are measured and transferred,
and how it is possible to produce very low concentrations of chemicals in
solution without producing liter quantities of potentially bioactive stock
solutions.
The protocol and design for this
experiment are again fairly simple. The
details and analysis required are more challenging.
Basically you will be trying to see if
you can figure how oxytocin acts to stimulate smooth muscle contraction in short
segments of mouse uterus by using the hormone alone or in combination with
drugs that are known to stimulate or inhibit various steps in transduction
cascades. To start, check your text for
the current model of the mechanism of action for oxytocin:
OT → stimulation of a G-coupled
receptor (Gαq) → stimulation of phospholipase – β → ↑ in IP3 & DAG → ↑
of intracellular Ca++ & activation of protein kinase C
Do note, however, that elevations of
DAG are often accompanied by increased activity of phospholipase A2 which leads
to release of arachidonic acid which is a substrate for cyclooxygenases 1 and 2
(Cox 1/Cox 2) which produce prostaglandins.
Prostaglandins are known to stimulate muscle contraction and act by binding
to G-coupled receptors of their own which can stimulate production of cAMP and
activation of protein kinase A.
So what’s most important here,
activation of the pKC path by OT or the pKA path by prostaglandins?
You should use the drugs with and
without added oxytocin to find out what steps are most crucial to
contraction. We will make stock
solutions of these drugs available for use in the lab (usually at micromolar or
microgram/mL concentrations) along with media to allow you to dilute them to
working concentrations. Before the lab
you will need to look up what these drugs do and what concentration is needed
for each of them to inhibit or stimulate the pathways involved. In using these compounds on tissues you are
best advised to add the needed amount of drug in a total of 50 uL of media to
the tissue already suspended in 5mL of unsupplemented media, i.e., any drug solution you make from
the stocks provided should be 100-fold more concentrated than the final,
working concentration you are intending to expose the tissue to. If you decide to add a drug and oxytocin to
the same mixture (e.g., to see if the
drug blocks the action of oxytocin), you should add them separately to the same
dish containing basal medium and unexposed tissue. Do not attempt to reuse tissue fragments once
they have been exposed to a drug and/or hormone. Be very careful in working with the concentrated
drugs and hormones. They are very potent!
Think gloves and glasses minimally.
You will again be working in small
groups on a simple bioassay system. This
time you will be looking at small segments of mouse uterus which contains
myometrial smooth muscle that has been exposed to estradiol. The muscle is normally a target for oxytocin
but becomes more sensitive to it under the influence of estrogens. The muscle responds to the presence of
oxytocin by contracting. You will be
able to observe a response within seconds of tissue exposure to the hormone and
you can quantitate that response by taking before and after measurements of
tissue length using a millimeter ruler or a caliper micrometer and computing
the percentage of tissue shortening that occurred. Both measures are made more precise by doing
the observation and measurement under a dissecting microscope.
The tissues will be dissected on the
morning of the lab from mice injected subcutaneously 3 days previously with 5
ug each of estradiol suspended in vegetable oil; several students may volunteer
to help with dissections and/or injections.
Dissections will be done in the surgical room in the animal care
suite. The uterine segments will be
placed into a simple culture medium such as Earle’s or Hank’s basal salt
solutions. They will be delivered to the
lab on ice and made available by the instructor as needed.
The approach is best designed as a
simple treatment versus non-treatment grid with no more than 8 grid cells aimed
at looking at one or two steps of the potential mechanistic pathway. If the class coordinates its efforts, you
should be able, collectively, to say whether the pKA or pKC paths are more
important in producing the contractions observed.
Sample treatment grid (one piece of
uterine tissue per cell, test cells may be repeated if time and tissue allow
it):
Uterine segment lengths in
mm
|
|
No drugs |
+ inhibitor 1 [xx] |
+ inhibitor 2 [yy] |
+ stimulator 1 [zz] |
||||
|
|
before |
after |
before |
after |
before |
after |
before |
after |
|
Without oxytocin added |
|
|
|
|
|
|
|
|
|
With oxytocin added |
|
|
|
|
|
|
|
|
After length data are collected,
compute any % changes in lengths, any averages and variances for replicated
treatment cells, and try to make sense of how these results correlate with the
suggested mechanisms of actions currently known for OT and prostaglandins. What drugs block or stimulate best? Try to answer the question about the relative
importance of the pKA versus the pKC pathway.
The summary for this experiment will
include: 1) the reasons for the drugs chosen; 2) the results grid reduced to %
change in tissue length and a decision on the effect of each drug (e.g.,
stimulates alone, inhibits alone, no effect alone, synergizes with OT, blocks
OT, no effect on OT); 3) a conclusion on the importance of the pKA versus the
pKC pathway for OT action. The summary
should be 2 pages long and include references cited.
|
Drug |
Known
target & action |
|
Caffeine |
Inhibits phosphodiesterase |
|
Isobutylmethylxanthine (IBMX) |
Inhibits phosphodiesterase |
|
Ibuprofen |
Inhibits Cox 1/2 |
|
Indomethacin |
Inhibits Cox 1/2 |
|
Phorbol 12-myristate 13-acetate |
Stimulates protein kinase C |
|
Staurosporin |
Inhibits protein kinases A, C, G |
|
Phloretin |
Inhibits protein kinase C |
|
Genistein |
Inhibits protein kinase C |
|
Dibutyryl cAMP |
Stimulates protein kinase A |
|
Calcium ionophore plus EGTA in media |
Decreases intracellular calcium |
|
Prostaglandin E1 |
Stimulates prostaglandin E1 receptors |
|
Polymyxin B sulfate |
Inhibits protein kinase C |
|
Drug |
Known target & action |
EC 50 |
Working Stock [ ] = 100xEC50 |
Storage Stock [ ] |
||
|
Oxytocin |
Smooth muscle contraction |
50
ng/min human; 10 ng/L = 10 pg/mL |
1
ug/L = 1 ng/mL |
10-20
ug/mL |
||
|
Caffeine |
Inhibits phosphodiesterase |
100
mg/L =
100 ug/mL |
10
mg/mL |
20
mg/mL |
||
|
Isobutylmethylxanthine
(IBMX) |
Inhibits phosphodiesterase |
5 mM = 5
umole/mL =
1111.2 ug/mL |
50
mg/mL |
50
mg/mL |
||
|
Ibuprofen |
Inhibits Cox 1/2 |
10
mg/L = 10
ug/mL |
1
mg/mL |
100
mg/mL |
||
|
Indomethacin |
Inhibits Cox 1/2 |
1
mg/kg = 1
mg/L = 1
ug/mL |
100
ug/mL |
10
mg/mL |
||
|
Phorbol
12-myristate 13-acetate |
Stimulates protein kinase C |
1 nM = 1 pmole/mL =
616.8 pg/mL |
61.68
ng/mL |
10
ug/mL |
||
|
Staurosporin |
Inhibits protein kinases A, C, G
|
10
nM = 10
pmole/mL = 4.6653 ng/mL |
1
nmole/mL |
100
nmoles/mL |
||
|
Phloretin |
Inhibits protein kinase C |
5 uM = 5
nmole/mL =
1371.35 ng/mL |
137.135
ug/mL |
10
mg/mL |
||
|
Genistein |
Inhibits protein kinase C |
15
uM = 15
nmole/mL =
4053.6 ng/mL |
250
nmoles/mL |
250
nmoles/mL |
||
|
Dibutyryl
cAMP |
Stimulates protein kinase A |
1
mM/L = 1
uM/mL= 491.4
ug/mL |
49.14
mg/mL |
50
mg/mL |
||
|
Calcium
ionophore plus
EGTA in media |
Decreases intracellular calcium |
1 uM
& 5 mM = 1
nmole/mL & 5 umole/mL =
523.62 ng/mL & 1901.75 ug/mL |
52.362
ug/mL & 250 mM |
100
ug/mL & 250
mM |
||
|
Prostaglandin
E1 |
Stimulates prostaglandin E1
receptors |
0.1
ng/mL |
10
ng/mL |
1
ug/mL |
||
|
Polymyxin
B sulfate |
Inhibits protein kinase C |
10
uM = 10
nmoles/mL =
13.8561 ug/mL |
1.38561
mg/mL |
100
mg/mL |
||
|
Anticipated Results of
Mechanism of Action Study |
||||||
|
Drug |
Known target & action |
Expected Result |
||||
|
Caffeine |
Inhibits phosphodiesterase |
↑ cAMP & ↑
Contraction |
||||
|
Isobutylmethylxanthine (IBMX) |
Inhibits phosphodiesterase |
↑ cAMP & ↑
Contraction |
||||
|
Ibuprofen |
Inhibits Cox 1/2 |
↓
Prostaglandin & ↓ Contraction |
||||
|
Indomethacin |
Inhibits Cox 1/2 |
↓
Prostaglandin & ↓ Contraction |
||||
|
Phorbol 12-myristate 13-acetate |
Stimulates protein kinase C |
↑ Contraction |
||||
|
Staurosporin |
Inhibits protein kinases A, C, G |
↓ Contraction |
||||
|
Phloretin |
Inhibits protein kinase C |
↓ Contraction |
||||
|
Genistein |
Inhibits protein kinase C |
↓ Contraction |
||||
|
Dibutyryl cAMP |
Stimulates protein kinase A |
↑ Contraction |
||||
|
Calcium ionophore plus EGTA in media |
Decreases intracellular calcium |
↓ Contraction |
||||
|
Prostaglandin E1 |
Stimulates
prostaglandin E1 receptors |
↑ Contraction |
||||
|
Polymyxin B sulfate |
Inhibits protein kinase C |
↓ Contraction |
||||
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