Timelines and the Nature of Science

Last week I saw tweets from @biogogy and @vB_ibbio about timelines for key developments in biological thinking and major developments in cell theory, respectively. Since it’s  been a while since I have posted here, I thought this would be a good way back into writing about the Nature of Science!

Timeline for the maturation of biology for #ibbio
What do you think biology teachers? pic.twitter.com/yOHe0m9meK

— Christian Moore Anderson (@biogogy) April 22, 2020

 

I’m trying to be much more explicit about connections within & between topics in #ibbio syllabus as I gradually update all of my slide decks & note templates. I’m almost done with topic 1 but virtual learning has caused a drastic change in the time I have!https://t.co/znFTnfdA47

— Gretel vB (@vB_ibbio) April 23, 2020

Following their lead, I have constructed timelines for all the scientists and their experiments that are explicitly mentioned in the Nature of Science notes.  Because of the number of experiments that took place in the 20th-century, I had to split it up into two separate timelines.

This links us to a classic TOK idea about the changing nature of knowledge, and in fact is referenced in the Nature of Science itself for topics 3.1 and B.4: “Developments in scientific research follow improvements in technology…” We can see this of course from the number of key experiments carried out in the 20th-century – these naturally followed on from developments in technology.  From a TOK perspective we might consider the role of technology in the production of scientific knowledge.  We might also look to the future and consider – what knowledge that we hold to be certain today, could be overturned in the future due to developments in technology?  It is an interesting discussion to have with your students and allows us to consider how scientific knowledge changes and is accepted.

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Nature of Science Practice – Cells

Here is a resource I will be using to help students learn and review the nature of science topics in Unit 4 – Cells (Topics 1.1, 1.2, 1.3, 1.4, 1.5).  This is an important topic for the Nature of Science, as the osmotic potential prescribed practical and Davson & Danielli have made multiple appearances on past exams – this is clearly an area to watch!

Using the Nature of Science in Class

With my current grade 11s, we have not spent much time on the nature of science in class.  Although resources are provided in their notes, we have focused more on experiments and content.  Having just finished our second unit and the end of unit test, I developed this resource as an introductory activity that students worked on in groups of three.

The resource is adapted from one of the many wonderful templates provided at the #TMSouthHistorians blog: https://tmsouthhistorians.wixsite.com/tmsouthhistorians/copy-of-blog-resources and often shared through @Jmosley_history – this is the A-B Starter.

 

I chose NOS prompts from topics 5.1, 5.2, 5.3, 10.3, 4.1, 2.1, 2.2, 2.3, 2.4, 2.5 and 8.1, which make up the first two units I teach – Diversity of Life and Chemistry of Life.  I had the students work together with no resources to begin with and try to identify links to the syllabus topics, TOK and to using the five categories of NOS to help organise the different ideas.  I tried to emphasise that they didn’t need to try and memorise new content but to discuss how these link to the knowledge they already have.  The task seemed to work well and got them more engaged than if we were just learning the content of the statements.  I hope to eventually develop templates for each unit that I teach.

 

2.4 Proteins

Looking for patterns, trends and discrepancies—most but not all organisms assemble proteins from the same amino acids.

Part of the universality of life is the observation that all living organisms construct proteins out of the same pool of 20 amino acids.  These 20 were identified in a rapid era of discovery after the development of partition chromatography in 1943.  However, this has now been expanded to include two additional amino acids – selenocysteine and pyrrolysine, giving a total of 22 amino acids.

Selenocysteine, as the name suggests, is similar to the amino acid cysteine but it has a Selenium atom as part of its side-chain (R-Group). It is a highly reactive and potentially dangerous substance – cells have to use some tricky metabolic pathways in order to prevent it from moving freely and building up in the cytoplasm.   It is used in certain redox reactions and has been found in all three domains of life, although it is not universal amongst them

Pyrrolysine is rarer, having only been found in some species of Archaeans and bacteria. It is structurally similar to lysine, but with the addition of a a pyrroline ring to the side-chain. It’s role and possible existence in other organisms is the focus of many ongoing studies.

Both of these amino acids are not encoded in the DNA – they are instead encoded by the stop codons UGA for selenocysteine and UAG for pyrrolysine and expressed via interactions with specific tRNA molecules, a process known as cotranslation. The biochemistry involved is fairly complex and difficult to summarise for IB biology purposes, but if you are interested the links below are a good place to start.

In summary, then:

• all living organisms use the traditional 20 amino acids to construct proteins and code for these amino acids in their DNA
• all three domains of life (thought not every species in them) also use a 21st amino acid selenocysteine in some proteins (humans included)
• Archaeans and bacteria have developed a mechanism to use a 22nd amino acid, pyrrolysine.
• both of these amino acids are not coded for in the DNA but are expressed through the use of a stop codon and tRNA
• the presence of Selenocysteine in all three domains strongly suggests it was present in the last universal common ancestor, and is thus a very ancient biochemical pathway

 

Selenocysteine and pyrrolysine are powerful examples of the versatility inherent in the genetic code. (Rother and Krzycki).

Like so many aspects of biology, once a rule is determined, the incredible variety of life shows us an exception.

For an interesting TOK-linked discussion, consider this quote, also from the Rother/Krzycki article:

They further provide examples of how precedent, though valuable, is not always the best predictor in scientific investigation…

What do the authors mean by this?  Does this mean that inductive reasoning is not always a reliable form of reason? What other examples from science can you think of to illustrate this quote?

Sources:

Das, Gunajyoti & Mandal, Shilpi. (2013). Nearest-Neighbor Interactions and Their Influence on the Structural Aspects of Dipeptides. Biochemistry research international. ResearchGate. Accessed on 2 October, 2018
https://www.researchgate.net/figure/Chemical-structures-of-selenocysteine-Sec-and-pyrrolysine-Pyl_fig1_258037372

Dinmann, J. (2012). Control of gene expression by translational recoding. Advances in Protein Chemistry and Structural Biology via ScienceDirect. Accessed on 2 October, 2018. https://www.sciencedirect.com/topics/neuroscience/pyrrolysine

Gutiérrez-Preciado, A., Romero, H. & Peimbert, M. (2010) An Evolutionary Perspective on Amino Acids. Nature Education. Accessed on 2 October, 2018.
https://www.nature.com/scitable/topicpage/an-evolutionary-perspective-on-amino-acids-14568445

Rother, Michael, and Joseph A. Krzycki. “Selenocysteine, Pyrrolysine, and the Unique Energy Metabolism of Methanogenic Archaea.” Archaea 2010 (2010): 453642. PMC. Web. 2 Oct. 2018.

9.1 Transport in the Xylem of Plants

Use models as representations of the real world—mechanisms involved in water transport in the xylem can be investigated using apparatus and materials that show similarities in structure to plant tissues.

This is another NOS that provides many links to the prescribed syllabus in Topic 9.1. In fact, you could teach many of the content using the potometer as a demonstration model, and then have students individually use their own and design their own independent variables etc.

• Prescribed Practical 7: Measurement of transpiration rates using potometers
• Application: Models of water transport in xylem using simple apparatus including blotting or filter paper, porous pots and capillary tubing;
• Skill: Design of an experiment to test hypotheses about the effect of temperature or humidity on transpiration rates.

Potometers can be as simple or technical as you like them to be.  A standard set-up might look something like this:

Basic Potometer (Pearson)

The general plant requirements are to use a woody stemmed-branch and that the leaves have a thin waxy cuticle.

The key to success is ensuring that there are no air bubbles in the tubing, as air bubbles will prevent the transpiration stream from working effectively.

If you have access to Vernier data loggers (or something similar) you can use a gas pressure sensor to record the rate of transpiration.  This can provide a more reliable quantitative measurement of the rate of transpiration and could be a good option for an Individual Investigation (IA).

Here are some pictures of the ones we set-up:

In the bottom right-hand corner you can see that the pressure in the tube is decreasing, indicating that transpiration is taking place.  We did some simple independent variables – removing leaves and changing the light intensity.  You could use a fan to try and stimulate a windier environment and small plastic bags on the leaves to increase humidity.  The advantage with a data logger is the ease of collecting the data and then analysing it, allowing for quick calculations of rate and other statistics.

Sources:

“LabBench Activity.” Design of the Experiment – Potometer, Pearson Education Inc., http://www.phschool.com/science/biology_place/labbench/lab9/design.html. Web. Accessed Feb 12, 2018.

“Measuring Rate of Water Uptake by a Plant Shoot Using a Potometer.” Practical Biology, Nuffield Foundation, http://www.nuffieldfoundation.org/practical-biology/measuring-rate-water-uptake-plant-shoot-using-potometer.Web. Accessed Feb 12, 2018.

9.3 Growth in Plants

Developments in scientific research follow improvements in analysis and deduction—improvements in analytical techniques allowing the detection of trace amounts of substances has led to advances in the understanding of plant hormones and their effect on gene expression.

In this case, the NOS statement is referring to the use of genomics to analyse gene expression in plants. Some of the earliest experiments into tropisms were conducted by none other than Charles Darwin, whose 1880 book The power of movement in plants represented the first attempt to synthesise available evidence on tropisms and included many of his own experiments in this field.  As developments in technology increased, the role of hormones became increasingly important and better understood.

Hormones influence gene expression; by detecting changes in gene expression, we can determine the role of hormones in this process. DNA sequences have been analysed to determine how these change in response to hormone exposure and mRNA levels (evidence of transcription and hence gene expression) can also be detected, pinpointing the cells that are responding to these hormones. Scientists have detected a range of common short sequences of nucleotides, from four to twelve bases in length. Different combinations of these appear to be linked to specific hormones and allow the genes to be affected by different classes of hormones. Details on some of these nucleotide sequences can be seen in the table below (Plants in Action).  Experiments have revealed that plant hormones can act extremely fast – with mRNA changes detected as quickly as 2-5 minutes from exposure.

Image from Plants in Action 1st Ed.

The advances in microarray analysis of DNA and mRNA was thus critical to our improved understanding of how plant hormones work.

Sources:

Jennifer J. Holland, Diana Roberts, Emmanuel Liscum; Understanding phototropism: from Darwin to today, Journal of Experimental Botany, Volume 60, Issue 7, 1 May 2009, Pages 1969–1978, https://doi.org/10.1093/jxb/erp113 Web. Accessed 6 Feb, 2018.

“Modified Gene Expression.” Plants in Action, 1st ed., Australian Society of Plant Physiologists, 1998, plantsinaction.science.uq.edu.au/edition1/?q=content/9-2-4-modi-ed-gene-expression. Web. Accessed 6 Feb, 2018.

9.2 Transport in the Phloem

Developments in scientific research follow improvements in apparatus—experimental methods for measuring phloem transport rates using aphid stylets and radioactively-labelled carbon dioxide were only possible when radioisotopes became available.

This NOS is another example that fits nicely into the syllabus content.  In 9.2, students are asked to analyse …data from experiments measuring phloem transport rates using aphid stylets and radioactively-labelled carbon dioxide. We can learn about this process through the NOS to understand how it works and why it enables us to understand the flow of sap through the phloem.  Two for the price of one!

Radioisotopes have been encountered before in your IB Biology studies. They become widely available to researchers after the second world war.  As the molecules that are radioactive can be traced, it became possible to track the flow of these molecules through cells, tissues and organisms over time.

Phloem transport is based on high hydrostatic pressure.  Thus if the phloem can be punctured, the contents should continue to exude out. If the plant is exposed to radioactively labelled carbon dioxide, the sap can be tested for the presence of the isotopes and the rate of translocation can then be estimated.

Image from D. Fischer, Plants in Action.

The use of the aphids can be summarised as follows (base on the images above; Plants in Action; image D. Fischer):

Top Image: Aphid feeding, inset is the stylet (St) penetrating to the phloem (p)
Image a: feeding aphid with stylet penetrating the plant
Images b-d: the stylet is removed from the aphid (they would be anaesthetised beforehand – there are some links here to the use of animals in experiments)
Image e: phloem sap starts to accumulate from the stylet.

The droplet of phloem sap can then be analysed for traces of the isotope to determine transport rate.  Aphids can be placed along the length of the plant stem to show transport along various distances.

Sources:

Fischer, D. “Collection of Sap from Aphid Stylet.” Plants in Action, University of Queensland, 2018, plantsinaction.science.uq.edu.au/content/522-techniques-collect-phloem-sap. Digital image. Feb 1, 2018.

“5.2.2 – Techniques to Collect Phloem Sap.” Plants in Action, Australian Society of Plant Scientists, 2018, plantsinaction.science.uq.edu.au/content/522-techniques-collect-phloem-sap. Online Textbook. Feb 1, 2018.

4.2 Energy Flow

Use theories to explain natural phenomena—the concept of energy flow explains the limited length of food chains.

Energy flow is governed through the laws of thermodynamics.  The first law (and I’m paraphrasing) essentially says that energy cannot be created or destroyed but merely transformed from one form to another.  The second law (the one about entropy) says that energy transfer is never 100% efficient and some energy is always lost as heat, which can not be regained or reused.

Therefore, in a food chain, light energy is transformed into chemical energy by producers and then into additional chemical forms as it passes through to consumers. As energy is being transformed at each trophic level, some of this energy is lost to the system (mostly as heat from respiration, but also in the form of undigested parts, excretion etc).  Thus while the total energy remains the same as the amount put in by the sun,  the amount that is actually available to consumers decreases with each increase in trophic level.  We use the figure of 10-20% as a rough rule of thumb – that is, at each successive trophic level, only 10-20% of the energy from the previous level is available. So 10% of the energy in a producer is available to a primary consumer, but only 10% of this energy is available to a secondary consumer – 1% of the original energy in the producer. Thus the higher the trophic level, the less energy is available and the limited length of most food chains and why many organisms can function at multiple trophic levels.

 

4.1 Species, Communities and Ecosystems

Looking for patterns, trends and discrepancies—plants and algae are mostly autotrophic but some are not. 

This is another NOS post that deals with the never-ending exceptions that arise whenever we seem to encounter a biological rule!

Back in Topic 5.3 (Classification) we learn that Kingdom Plantae is defined as containing organisms that are multicellular, photosynthetic and eukaryotic. Photosynthetic cells implies that the organism is autotrophic, but it turns out that this is not always the case!

The obvious exception would appear to be the carnivorous plants, such as the Venus Fly Trap (Dionaea muscipula) or the pitcher plant (such as Cephalotus sp.).

Cephalotus follicularis – the Albany Pitcher Plant

Venus Flytrap (Dionaea muscipula)

However, these plants retain their photosynthetic abilities and can even be raised successfully without providing any insects for them to eat (Rice). According to Rice (2007), this makes them only partially heterotrophic, as they still derive a large proportion of their energy from photosynthesis.

The true heterotrophic plants are those that are parasitic or saproptrophic.  A great example of a parasitic plant is Rafflesia arnoldii, the plant that produces the largest flower in the world.  It is a parasite of certain jungle vines and produces no roots, shoots or stem.  In fact, it is only visible when it flowers.  It gains all its nutrition through its parasitism of the host plant.

Similarly, there is a bewildering diversity amongst algae of organisms that are facultative and obligate heterotrophs. Many of these species have, like Rafflesia, become parasites, such as the genera Helicosporidium and Prototheca. Others, such as the fascinating genus Polytomella, have four flagella and are motile heterotrophs.

Polytomella

As always, biology refuses to be put into a box!

Sources:

Davis, Troy. “ Fully Open Flower of Rafflesia Arnoldii.” Rafflesia Arnoldii Robert Brown, Southern Illinois University, 29 Oct. 2010, parasiticplants.siu.edu/Rafflesiaceae/Raff.arn.page.html.

Figueroa-Martinez, F., Nedelcu, A. M., Smith, D. R. and Reyes-Prieto, A. (2015), When the lights go out: the evolutionary fate of free-living colorless green algae. New Phytol, 206: 972–982. doi:10.1111/nph.13279

“Polytomella.” Polytomella, EOL, http://www.eol.org/pages/90494/details.

Rice, Barry. “Are Carnivorous Plants Autotrophic or Heterotrophic?” The Carnivorous Plant FAQ: Autotrophic or Heterotrophic?, Jan. 2007, http://www.sarracenia.com/faq/faq1100.html.

“The Albany Pitcher Plant.” Cephalotus Follicularis – the Albany Pitcher Plant, Botanical Society of America, botany.org/Carnivorous_Plants/Cephalotus.php.

“Venus Fly Traps (Dionaea Muscipula).” The Mysterious Venus Flytrap, Botanical Society of America, botany.org/bsa/misc/carn.html.

2.5 Enzymes

Experimental design—accurate, quantitative measurements in enzyme experiments require replicates to ensure reliability. (3.2)
This links to Practical 3 – Experimental investigation of a factor affecting enzyme activity.

Working with enzymes is something that all biology students get very familiar with over their studies!  This is particular true in the new syllabus as Practical 3 requires an enzyme experiment and they are popular as topics for the IA.

Testing the effect of substrate concentration on potato catalase.

Although there are several other practical-themed NOS statements, this one makes particular reference to the idea of reliability and replicates.  In terms of assessment this is most likely to appear in the Section A of Paper 3, when students are provided with experimental scenarios and have to apply their knowledge. However, it is also important for the IA.  The chosen investigation must design a methodology that will collect sufficient data, the data must be processed with appropriate awareness of uncertainties, and the reliability of the results reviewed and evaluated in the conclusion and evaluation.

This is thus an important lesson to not just experience the practical side of biology, but to understand the importance of replicates and how this impacts the IA.  So what could this look like? Here are a few ideas:

• If an enzyme-based experiment, aim for five variations of the independent variable (five different pHs; five different temperatures etc). As enzyme experiments are invariably time-based, this will allow you to plot a graph with more confidence (five data points rather than, say, three).
• Try to repeat each variation five times.  This will provide enough data to calculate the average and standard deviation. Of course there are more processing options than this (think rate of reaction) but these two are the basics.
• The conclusion/evaluation needs to then assess how the range of the independent variable, the sample size and the processed data contribute to the reliability of the experiment. The more replicates you have, the more robust this section will be.
• There are always time constraints on how many replicates you can collect – so factor this into your methods.  If your experiment is only collecting data for three minutes for each run, then you should be able to get more replicates (and you will be expected to collect more data).  If, in contrast, you are collecting data for more than an hour per experiment, then you will need to be aware of this.
• Finally, remember that design, processing and evaluation are all relative to the specific experiment you carried out – so always think in terms of the context for your investigation and the resources available to you.