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6.21: Human Population - Biology

6.21: Human Population - Biology



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How do humans adapt to their environment?

It could be said that the human population does not have to adapt to its environment, but forces the environment to change to suit us. We can live practically anywhere we want, eat all types of food, and build all types of housing. Because of all of these "adaptations," our population has grown, after a slow start, considerably fast.

The Human Population

Humans have been called the most successful "weed species" Earth has ever seen. Like weeds, human populations are fast growing. They also disperse rapidly. They have colonized habitats from pole to pole. Overall, the human population has had a pattern of exponential growth, as shown in Figure below. The population increased very slowly at first. As it increased in size, so did its rate of growth.

Growth of the Human Population. This graph gives an overview of human population growth since 10,000 BC. It took until about 1800 AD for the number of humans to reach 1 billion. It took only a little over 100 years for the number to reach 2 billion. The human population recently passed the 7 billion mark! Why do you think the human population began growing so fast?

Early Population Growth

Homo sapiens arose about 200,000 years ago in Africa. Early humans lived in small populations of nomadic hunters and gatherers. They first left Africa about 40,000 years ago. They soon moved throughout Europe, Asia, and Australia. By 10,000 years ago, they had reached the Americas. During this long period, birth and death rates were both fairly high. As a result, population growth was slow.

Humans invented agriculture about 10,000 years ago. This provided a bigger, more dependable food supply. It also let them settle down in villages and cities for the first time. The death rate increased because of diseases associated with domestic animals and crowded living conditions. The birth rate increased because there was more food and settled life offered other advantages. The combined effect was continued slow population growth.

Summary

  • Early humans lived in small populations of nomadic hunters and gatherers. Both birth and death rates were fairly high. As a result, human population growth was very slow.
  • The invention of agriculture increased both birth and death rates. The population continued to grow slowly.

Review

  1. Describe human population growth rates.
  2. How did the invention of agriculture affect human birth and death rates? How did it affect human population growth?

2.1 Human Genetics

Biological researchers study genetics in order to better understand why individuals develop different physical traits, and psychological researchers study genetics in order to better understand the biological basis that contributes to certain behaviors. While all humans share certain biological mechanisms, we are each unique. And while our bodies have many of the same parts—brains and hormones and cells with genetic codes—these are expressed in a wide variety of traits, characteristics, behaviors, thoughts, and reactions.

Why do two people infected by the same disease have different outcomes: one surviving and one succumbing to the ailment? How are genetic diseases passed through family lines? Are there genetic components to psychological disorders, such as depression or schizophrenia? To what extent might there be a psychological basis to health conditions such as childhood obesity?

To explore these questions, let’s start by focusing on a specific disease, sickle-cell anemia , and how it might affect two infected sisters. Sickle-cell anemia is a genetic condition in which red blood cells, which are normally round, take on a crescent-like shape (Figure 1). The changed shape of these cells affects how they function: sickle-shaped cells can clog blood vessels and block blood flow, leading to high fever, severe pain, swelling, and tissue damage.

Figure 1. Normal blood cells travel freely through the blood vessels, while sickle-shaped cells form blockages preventing blood flow.

Many people with sickle-cell anemia—and the particular genetic mutation that causes it—die at an early age. While the notion of “survival of the fittest” may suggest that people suffering from this disease have a low survival rate and therefore the disease will become less common, this is not the case. Despite the negative evolutionary effects associated with this genetic mutation, the sickle-cell gene remains relatively common among people whose ancestors originated in specific parts of Central Africa, the Indian subcontinent and the Middle East. Why is this? The explanation is illustrated with the following scenario.

Imagine two young women—Luwi and Sena—sisters in rural Zambia, Africa. Luwi carries the gene for sickle-cell anemia Sena does not carry the gene. Sickle-cell carriers have one copy of the sickle-cell gene but do not have full-blown sickle-cell anemia. They experience symptoms only if they are severely dehydrated or are deprived of oxygen (as in mountain climbing). Carriers are thought to be immune from malaria (an often deadly disease that is widespread in tropical climates) because changes in their blood chemistry and immune functioning prevent the malaria parasite from having its effects. However, full-blown sickle-cell anemia, with two copies of the sickle-cell gene, does not provide immunity to malaria.

While walking home from school, both sisters are bitten by mosquitos carrying the malaria parasite. Luwi does not get malaria because she carries the sickle-cell mutation. Sena, on the other hand, develops malaria and dies just two weeks later. Luwi survives and eventually has children, to whom she may pass on the sickle-cell mutation.

Link to Learning

Malaria is rare in the United States, so the sickle-cell gene benefits nobody: the gene manifests primarily in health problems—minor in carriers, severe in the full-blown disease—with no health benefits for carriers. However, the situation is quite different in other parts of the world, particularly in tropical climates near the equator. In parts of the world where malaria is prevalent, having the sickle-cell mutation does provide health benefits for carriers (protection from malaria).

This is precisely the situation that Charles Darwin describes in the theory of evolution by natural selection (Figure 2), which you learned about in the previous section of this book. In simple terms, the theory states that organisms that are better suited for their environment will survive and reproduce, while those that are poorly suited for their environment will die off. In our example, we can see that as a carrier, Luwi’s mutation is highly adaptive in her environment however, if she resided in the United States (where malaria is much less common), her mutation could prove costly—with a high probability of the disease in her descendants and minor health problems of her own.

It is important to remember, that while sickle-cell anemia alleles are common in some parts of Africa and other parts of the world, this pattern in the geographical distribution of alleles does not mean that sickle-cell anemia is a trait associated with any particular race. Race is a social construct, and not a biological concept.

Figure 2. (a) In 1859, Charles Darwin proposed his theory of evolution by natural selection in his book, On the Origin of Species. (b) The book contains just one illustration: this diagram that shows how species evolve over time through natural selection.


Examples of Populations

African Elephants

There are two traditionally recognized species of elephant, African elephants (Loxodonta Africana) and Asian Elephants (Elephas maximus), although recent research has divided the African elephants into two species: the African bush elephants (Loxodonta africana) and the African forest elephants (Loxodonta cyclotis).

Populations of African elephants are believed to have existed on a continental-wide scale, numbering up to 5 million individuals in the early 1900s. However, due to habitat fragmentation and poaching for their tusks, elephant numbers have suffered severe declines. There are now believed to be around 400,000 remaining African elephants.

Elephant group structure is formed of family units of around 10 individuals, although when elephant families come into contact, they may bond to form larger groups – called ‘herds’ – of up to 100. Each of these herds forms a local population. However, any individual from each species could reproduce with another species member, so the full population of each African species includes all the individuals on the continent.

Pond Populations

Within a habitat there can be many different populations a small-scale example is a lake. A lake may provide a habitat for birds, fish, insects, amphibians and mammals such as otters or rats. Although each species is provided with resources from the lake, their populations are likely to rely on the habitat in unique ways. For fish, land presents an impenetrable barrier for dispersal. Without any way of leaving, an entire population of trout may exist solely within the lake and nowhere else.

Amphibians such as toads may spawn in the lake, and use several nearby lakes within a valley for feeding. However, because they cannot get across mountains, their local population is restricted to the inside of the valley. If environmental conditions within the valley differ from other surrounding valleys, and the toads are isolated from other populations of the same species for long enough, the behavior or morphology of the toad may change sufficiently enough so that it cannot mate with toads outside of the valley. This isolation would drive the process of speciation and thus the formation of new species.

Migrating birds may visit the lake seasonally in order to winter for part of the year, these birds form a local population. When the birds return from their wintering grounds, they meet with other populations of the same species so that they can breed in larger numbers. It is common for birds of different ages or sexes to migrate at different times or distances, so the population sizes depend on the group demography.

Salmon

Many species of Salmon are anadromous, which means they are born in fresh water before migrating to the ocean to feed and mature, and return to fresh water to breed.

Salmon tend to return to the same river that they were born in, in order to themselves spawn. Because of this strong desire to ‘home’, salmon usually do not stray far away from their native spawning site, although the dispersal distance depends largely on the particular species.

Because most spawning sites are separated by land or deep water, each group of salmon that are born in a certain spawning site makes up the local population within that site although the conditions within the routes available for dispersal to other sites are not impossible for the salmon to withstand, they are rarely found to move between sites.

During their time spent at sea, salmon come into contact with salmon from other local populations, even very distant ones. Although there are no barriers to mating between local populations of the same species, the tendency of salmon to return to their natal river greatly reduces gene flow between them. Nonetheless, some individuals do stray from the expected route, either by choice or in error, resulting in some gene flow between populations.

Due to their life history cycle, salmon can be categorized within the metapopulation structure.


Human Population

Population Growth rate
History of Human Population
-Human populations were kept in check by diseases, famines and wars until the middle ages ex: Infanticide, Bubonic Plagues
-Populations began to increase rapidly after A.D. 1600 (Increased sailing and navigating skills, agricultural developments, better sources of power, better health care and hygiene)
-We are now in a J-curve, population is increasing at an exponential rate. Our present population is 6.6 billion people and growing by 100 million people per year.

Demographics-vital statistics about people (births, deaths, where people live, total population size)
1) Crude Birth rate-the number of births in a year per thousand persons
2) Crude Death rate-the number of deaths per thousand persons in any given year
3) Life Expectancy-the average age that a newborn infant can expect to attain in any given society
To calculate the annual rate of population growth subtract the crude death rate from the crude birth rate and divide by 10.

The replacement fertility rate is the number of children a couple must have to keep the population stable. In the third world it is 2.7, in the US it is 2.1.
-Developing countries have seen the greatest progress
-Discrepancies in how benefits are distributed within a country are shown by varying life expectancies at different areas in a country
-Annual income has a strong correlation to life expectancy
Developing Countries-residents live for about twice as long as they used to
Developed Countries-increase not as great because it was higher to begin with

Impact on Resources-The more people there are, the more resources are used. Especially in developed countries like the U.S. where the amount of resources used per person is greater then in less developed countries.

Carrying Capacity-local, regional and global
-The number of individuals who can be supported in a given area within natural resource limits, and without degrading the natural social, cultural and/or economic environment for present and future generations. As the environment is degraded, carrying capacity gets smaller. The maximum carrying capacity for humans on the Earth is 13-15 billion. The average ecological footprint an American makes is approximately 12 acres/person. Our footprint is the number of acres required to meet the resource needs of an individual.

Population Projections and Solutions
-There could be a population overshoot past the carrying capacity and then a die-off or we could adjust our population growth to an S-curve

-Estimated Demographic Transitions-from high birth and death rates to lower birth and death rates due to improved living conditions and economic development

-Cairo Conference-179 countries met in 1994 to develop an action plan to deal with population growth and included issues such as poverty and health care
-5 Basic Components
1) Provides family-planning services
2) Promotes free trade, private investment, and assistance to countries that need help.
3) Addresses issues of gender equity.
4) Addresses issues of equal access to educational opportunity.
5) Educates men.

*Female Education and Economic Status-If females are educated about birth control, and made aware that they do not need to have many children to replace them, they will not have as many babies. Also, if their economic status is improved, many women will get jobs instead of having children

-Family Planning
-Fertility Decline in Rich Countries
-Abortion-RU486, methotrexate, misprostol, surgical abortion
-Avoidance-Body temp. technique, celibacy/abstinence
-Barrier-Condom, diaphragm, cervical cap, vaginal sponge, spermicide, IUD
-Chemical-"The Pill"
-Surgical-Tubal litigation, vasectomy


Results

SOX5/6/21 expression is increased in brain NSCs upon oncogenic stimuli

To address the role of SOX5/6/21 in brain NSCs upon oncogenic stress, we first defined their expression pattern and activity in NSCs of the adult mouse SVZ, which have been shown to be susceptible to oncogenic transformation (24–26). In this region of the brain, a vast majority of the SOX2 + and NESTIN + progenitor cells expressed SOX5/6/21, and their expression could be detected in most self-renewing KI67 + cells (Fig. 1A–K). Overexpression of SOX5/6/21 promotes cell-cycle exit of embryonic NSCs (Supplementary Fig. S1A and S1B refs. 13, 14). To examine whether this function is conserved in the adult brain, SVZ cells were isolated and transduced with lentiviruses expressing GFP or SOX5/6/21 (Fig. 1L). Consistent with their function in embryonic cells, the fraction of adult NSCs that were labeled by a 1 hour pulse of EdU, 72 hours posttransduction, was reduced to less than half that of NSCs expressing GFP only (Fig. 1M).

SOX5/6/21 expression in the SVZ is increased by oncogenic stimuli. A–I, Coexpression of SOX5/6/21 (red A–I) with the progenitor markers SOX2 (green A–C), NESTIN (green D–F), and KI67 (green G–I) in the mouse SVZ. J and K, Graphs show percentage of SOX2 + cells (J) and KI67 + cells (K) expressing SOX5/6/21 in NSCs of the adult SVZ (n = 6–7 and n = 3 sections, respectively). L and M, Proliferation of SOX5/6/21-transduced SVZ cells was quantified as the percentage of GFP-positive cells labeled with EdU (n = 5–6). N–P, Immunoblots showing NESTIN and SOX protein levels in cultured mouse SVZ cells (O) after transduction with lentiviruses expressing the oncogenes AKT1 and H-RAS in a CRE-dependent manner (n = 3). Bar graph (P) shows fold-change expression of lenti-ARC over lenti-CRE and dotted line indicates a fold change of one. Scale bars in A–I, 20 μm M, 50 μm. For all graphs, data are shown as mean ± SEM. *, P < 0.05 **, P < 0.01.

The finding that high levels of SOX5/6/21 possess the capacity to reduce cell proliferation prompted us to examine their expression levels in adult NSCs in response to oncogenic stimuli. To address this, SVZ cells were isolated (Fig. 1L) and transduced with lentiviruses expressing CRE enzyme, with or without CRE/loxP-controlled lentiviruses expressing the oncogenic forms of AKT and H-RAS (AKT, H-RAS, and CRE, hereafter referred to as ARC Fig. 1N Supplementary Fig. S1C), which have been shown to induce a malignant phenotype in the mouse brain (25). Interestingly, while the expression levels of the general NSC markers SOX2 and NESTIN remained unchanged following ARC-transduction, the levels of SOX5/6/21 proteins were increased 5 to 7-fold in comparison with cells expressing the CRE-enzyme only (Fig. 1O and P).

Deletion of Sox5/6/21 potentiates the formation of glioma-like tumors

The antiproliferative activity of SOX5/6/21 and the observation that their expression levels were increased in NSCs transduced with ARC-expressing lentiviruses, raise the possibility that these proteins may be part of a cellular response mechanism, which counteracts oncogenic transformation of NSCs. To examine this possibility, we analyzed how the tumor-inducing capacity of AKT and H-RAS, in NSCs of the adult brain was affected by the loss of SOX5/6/21 expression. Lentiviruses expressing ARC (Fig. 1N) were injected into the SVZ (Fig. 2A) of adult wild-type (Wt) mice or mice conditionally mutant for Sox5 (20), Sox6 (21), or Sox21 (see Supplementary Materials and Methods), as well as into mice harboring various combinations of these mutations. Apart from efficiently activating AKT and H-RAS expression from the CRE/loxP-controlled vectors (Fig. 2B–D), the virally expressed CRE-enzyme also successfully reduced SOX5/6/21 expression in the transduced SVZ cells (Fig. 2E and F Supplementary Fig. S2A). In accordance with previous observations (25), the majority of the Wt brains showed no tumor formation, or only the development of minor hyperplasia, 4 to 5 months after ARC misexpression (Fig. 2G Supplementary Table S1), and tumor formation could only be detected in approximately 15% of the treated Wt animals. In contrast, misexpression of ARC in mice conditionally mutant for Sox5, Sox6, or Sox21, or for combinations of these genes, lead to tumor formation in around 60% to 80% of the transduced brains (Supplementary Table S1). Moreover, as determined with GFP-expression, as well as with hematoxylin and eosin (H&E) staining, the tumors were significantly larger in brains of the combinatorial mutants, compared with tumors generated in the individual mutants, with the largest tumors detected in Sox5/6/21–mutant mice (Fig. 2G–O). Importantly, in the absence of oncogene expression, a CRE-based excision of Sox5/6/21 did not lead to any tumor formation 5 months after the injection of CRE-expressing lentivirus (Supplementary Fig. S2B–S2I). Also, the additive effect that combinatorial loss of Sox5/6/21 had on tumor growth indicates that these SOX proteins have partly overlapping activities. Consistent with this, tumor formation in ARC-transduced Sox5/6- or Sox21-mutant mice could be prevented by the coinjection of SOX21- and SOX6-expressing lentiviruses, respectively (Supplementary Fig. S2J–S2M). Thus, although the deletion of Sox5/6/21 does not lead to any detectable growth anomalies, these loss-of-function experiments demonstrate that SOX5/6/21 possess overlapping activities in preventing oncogene-induced tumor formation in the SVZ.

Oncogene-driven transformation of SVZ cells lacking SOX5/6/21. A–D, Injection of ARC-expressing lentiviruses (Fig. 1N) into the adult mouse SVZ (A) results in the expression of GFP (B–D green), AKT-HA (C red), and H-RAS-Flag (D red). E and F, Two weeks after injection of ARC-expressing lentiviruses, transduced cells express normal levels of SOX2 (E red), but only low levels of SOX21 (F red). G–O, GFP expression in tumors (G–J green) and their cellular density visualized by H&E (K–N). O, Tumor size based on GFP-positive area at the same rostro-caudal level (n = 8–10 sections in 5–10 tumors). P–T, ARC-induced tumors in Sox5/6/21 fl/fl animals analyzed with H&E. High cellular density (Q), bleedings (R), and large dilated vessels (S) are shown. CD31 + vascular endothelial cells within the GFP + tumor mass (T). U–Y, NESTIN, VIMENTIN, GFAP, PDGFRA, and NG2 expression in ARC-induced tumors in Sox5/6/21 fl/fl mice. Scale bars in B–F, 20 μm K–N, Q–T, U–Y, 50 μm G–J, P, 1 mm. For all graphs, data are shown as mean ± SEM. **, P < 0.01 ***, P < 0.001.

Examination of H&E-stained tumor sections revealed characteristics typical of human high-grade gliomas, including increased cellular density, hemorrhage, cellular atypia, and microvascular proliferation (Fig. 2P–T ref. 25). These features were most abundant in those tumors generated in combinatorial Sox5/6/21–mutant mice, and to a lesser extent in tumors of mice mutant for Sox5/6 or Sox21. Oncogenic H-RAS and AKT have previously been demonstrated to induce astrocytic gliomas (27). In accordance, apart from expressing the NSC marker NESTIN, the tumors generated in Sox5/6/21–mutant mice were also highly positive for the astrocytic markers VIMENTIN and GFAP (Fig. 2U–W). However, the tumors also expressed high levels of the oligodendrocyte precursor markers PDGFRA and NG2 (Fig. 2X and Y). Similar composition of markers was found in tumors generated in the brains of Wt animals (Supplementary Figs. S2N–S2R), independent of the loss of the Sox5/6/21 genes.

Loss of Sox5/6/21 deregulates genes promoting tumor proliferation

To examine how the loss of SOX5/6/21 expression facilitates oncogenic transformation of NSCs, SVZ cells of Wt mice or mice conditionally mutant for Sox5/6, Sox21, or Sox5/6/21 were isolated and characterized in neurosphere-forming assays, 2 weeks after injection of lentiviruses expressing ARC. Compared with cells from Wt mice, cells isolated from Sox5/6-, Sox21-, and Sox5/6/21–mutant mice generated a significantly higher number of neurospheres per ARC-expressing cell, with Sox5/6/21–mutant cells exhibiting the highest sphere-forming capacity (Fig. 3A–E). Moreover, while we could not detect any significant increase in the volume of the neurospheres generated by Sox5/6–mutant cells, compared with those generated by Wt cells transduced with ARC-expressing lentiviruses, the loss of SOX21 expression, or SOX5/6/21 expression, increased the volume of the neurospheres over two and seven times, respectively (Fig. 3A–D and F). In agreement with these observations, the fraction of DAPI + or KI67 + ARC-expressing cells that incorporated EdU during a 1-hour pulse, was increased more than 30% in Sox21-mutant neurospheres and more than 60% in Sox5/6/21–mutant neurospheres, compared with Wt or Sox5/6–mutant neurospheres (Fig. 3G–K). Thus, the proliferative capacity of oncogene expressing SVZ cells is substantially increased upon the loss of Sox5/6/21.

SOX5/6/21 suppress genes promoting tumor proliferation. A–K, Neurosphere forming capacity and proliferation of SVZ cells isolated from mouse brains 2 weeks after the injection of ARC-expressing lentiviruses. Sphere size (A–D) and proliferation (H–K) were measured after 10 to 14 days of culture. E–G, Quantifications of formed neurospheres (E n = 6), sphere volume (F n = 17–22 neurospheres/group) and proliferation (G n = 5–7). L and M, GO analysis of deregulated genes in ARC-expressing neurospheres lacking Sox5/6/21 compared with ARC-expressing Wt spheres. Biological processes (solid bars) and pathways (stippled bars). N and O, GO analysis of gene sets commonly deregulated in ARC-expressing neurospheres and in human high-grade glioma, compared with low-grade glioma. X-axes show significance of enrichment. Scale bars in H, 50 μm D, 100 μm. For all graphs, data are shown as mean ± SEM. *, P < 0.05 **, P < 0.01 ***, P < 0.001.

Next, we used RNA-seq analysis to assess how the loss of Sox5/6/21 affects the gene expression profile of ARC-expressing SVZ cells. In comparison to Wt cells transduced with ARC-expressing lentiviruses, the loss of SOX5/6/21 expression lead to an upregulation (>1.5-fold) of 993 genes and a downregulation (>1.5-fold) of 998 genes. Consistent with the findings above, gene ontology (GO) analysis of the deregulated genes revealed a significant upregulation of proliferation-associated genes, resulting in high enrichment of GO-terms such as “Mitotic cell cycle,” “Cell division,” and “RB in cancer” (Fig. 3L). In contrast, analysis of the downregulated genes resulted in a strong enrichment of GO-terms associated with cellular differentiation, such as “Neurogenesis,” “Gliogenesis,” and “Axon guidance pathway” (Fig. 3M). Interestingly, of the genes upregulated both in ARC-expressing Sox5/6/21 mutant cells and in human GBM compared to low-grade glioma (28), we detected many genes implicated in cell-cycle regulation and tumorigenesis (e.g., AURKA, FOXM1, E2F8, MELK, PLK1, BIRC5 Fig. 3N Supplementary Table S2 refs. 29–33). In contrast, among the genes commonly downregulated in these different cell types, we detected several genes with relevant roles in neuronal differentiation and tumor suppression (e.g., EBF4, DLL1-2, PTCH1, NF1, FAT1, APC, BAI1 Fig. 3O Supplementary Table S2 refs. 34–40). Hence, Sox5/6/21 appear to prevent oncogene-expressing SVZ cells from upregulating pro-proliferative genes that are highly expressed in human GBM.

Antitumorigenic responses by SVZ cells require SOX5/6/21

Components of the cyclin–CDK–RB axis are important regulators of tumor proliferation. Although cyclin/CDK complexes promote proliferation by inactivating the tumor suppressor protein RB (41), CDK inhibitors block this activity, and thus counteract proliferation (3). As revealed by immunoblotting, in the absence of oncogenes, the loss of Sox5/6/21 did not significantly alter the protein levels of cyclin D1, -D2, -E1, or -A1 in cultured SVZ cells (Supplementary Fig. S3A). However, in the presence of AKT and H-RAS expression, the loss of Sox5/6/21 lead to a dramatic increase in cyclin levels (Fig. 4A). Cells expressing ARC responded differently to the loss of Sox5, Sox6, and Sox21. Although the upregulation of cyclin D2 and cyclin E1 levels were predominately associated with the loss of Sox21, the most significant increase in cyclin A1 levels was detected in Sox5/6–mutant cells (Fig. 4A). Even though the level of total RB remained unchanged, the level of the inactive, hyperphosphorylated form of this protein (pRB) followed that of the cyclins, and was highly increased in ARC-expressing cells mutant for Sox5/6, Sox21, and Sox5/6/21 (Fig. 4B). In the absence of oncogene expression, the loss of Sox5/6/21 did not lead to a significant change in pRB levels (Supplementary Fig. S3B). Moreover, although the protein levels of the CDK inhibitors p21, p27, p57, and the tumor suppressor p53 were increased in SVZ upon AKT and H-RAS expression (Supplementary Fig. S3C), this upregulation was completely abolished following the loss of Sox5/6/21 (Fig. 4C). In the absence of oncogene expression, the lack of Sox5/6/21 did not lead to detectable decrease in protein levels of CDK inhibitors or p53 (Supplementary Fig. S3D). Notably, a corresponding regulation of the cell-cycle regulators analyzed above could not be detected at the mRNA levels (Supplementary Table S2).

SOX5/6/21 are required for tumor suppressor upregulation. A–C, Protein levels of cell-cycle regulatory proteins in neurospheres derived from SVZ cells of mice injected with ARC-expressing lentiviruses. D–H, Expression of p21 (E), p27 (F), or p53 (G) prevents growth of ARC-expressing SVZ-derived neurospheres (H n = 20–22 neurospheres/group). I–M, Sox5/6/21 fl/fl brains 1 month after the injection of ARC-expressing lentiviruses (I) with or without lentiviruses expressing p21 (J), p27 (K) or p53 (L). Quantification of tumor size as measured by GFP area (M n = 7–9). Scale bars in G, 200 μm L, 1 mm. For all graphs, data are shown as mean ± SEM. *, P < 0.05 ***, P < 0.001.

One possibility is that the inability of Sox5/6/21 mutant SVZ cells to upregulate CDK inhibitors and p53 could explain their extensive proliferative activity and their susceptibility to malignant transformation in response to oncogenes. Consistently, restoring the expression levels of p21, p27, or p53 in Sox5/6/21–mutant SVZ cells transduced with ARC-expressing lentiviruses, significantly reduced their neurosphere-forming capacity (Fig. 4D–H). Moreover, lentiviral-based expression of p21, p27, or p53 substantially reduced or totally prevented ARC-induced tumor formation in Sox5/6/21 mutant mice (Fig. 4I–M). Hence, restoring high levels of p21, p27, and p53 blocks oncogene-induced transformation of Sox5/6/21 mutant SVZ cells.

High SOX5/6/21 levels block tumor-inducing capacity of human GBM cells

Consistent with their capacity to counteract proliferation of mouse NSCs, forced expression of SOX5/6/21 in human primary (KS4 and G3) GBM cells or an established (U87) GBM cell line, significantly decreased the fraction of EdU incorporating cells, compared with those cells expressing GFP only (Figs. 5A–E Supplementary Fig. S4A and S4B).

High levels of SOX5/6/21 block tumor-inducing capacity of human GBM cells. A–E, High levels of SOX5/6/21 decrease proliferation of human GBM cells 3 days posttransduction (A–D). FACS-based quantification of proliferation of GBM cells overexpressing SOX5/6/21 (E n = 4). F, FPKM expression levels of SOX5/6/21, normalized against PCNA, in low-grade glioma (grade II/III) and high-grade glioma (grade IV n = 31–33 samples). G–K, Injection of human GBM cells transduced with lentiviruses expressing GFP, SOX5-GFP, SOX6-GFP, SOX21-GFP into striatum of adult NOD-SCID mice. Scale bars in D, 25 μm K, 1 mm. For all graphs, data are shown as mean ± SEM. **, P < 0.01 ***, P < 0.001.

The negative relationship between SOX5/6/21 levels and GBM cell proliferation raises the question if there is a similar negative correlation between the level of SOX5/6/21 expression and the malignancy grade in human gliomas. To address this possibility we retrieved publically available gene expression data sets of low-grade (grade II and III) and high-grade (grade IV) glioma samples analyzed with RNA-seq (28). Notably, the expression levels of SOX5/6/21 were decreased approximately four to six times in high-grade glioma samples compared to those of low-grade (Fig. 5F) and this reduction was independent of the mutational status of TP53 in the examined glioma samples (Supplementary Fig. S4C and S4D). Consistent with these findings, although transplantation of GFP-transduced human primary GBM cells (KS4) into the striatum of NOD-SCID mice (Fig. 5G) resulted in large tumors 3 months postinjection (Fig. 5H), GBM cells misexpressing either SOX5, SOX6, or SOX21, failed to form secondary tumors upon transplantation (Fig. 5I–K). Thus, apart from preventing mouse SVZ cells from malignant transformation, SOX5/6/21 can also reduce proliferation and the tumor-inducing capacity of human primary GBM cells.

SOX5/6/21 can restore tumor suppressor responses in human GBM cells

The fact that increased levels of SOX5/6/21 counteract proliferation of human GBM cells, both in vitro and in vivo, raises the possibility that SOX5/6/21 play a role in restoring an antitumorigenic expression profile in cancer cells that are already exhibiting a malignant profile. To address this hypothesis we analyzed the transcriptomes of five primary human GBM cell lines (KS4, G3, JM3, #87, and #89) and of the established glioma cell line U87 (42), 72 hours after transduction with SOX5/6/21-expressing lentiviruses (Supplementary Fig. S5A). The transduced cells responded to SOX5/6/21 expression by deregulating thousands of genes (>1.5-fold Fig. 6A Supplementary Fig. S5B). Comparisons of the up- and downregulated genes revealed a significantly higher overlap between the genes deregulated by SOX5 and SOX6, compared with the genes deregulated by SOX21 (Fig. 6B Supplementary Fig. S5C). GO-term analysis of genes deregulated by SOX5/6/21 in the primary and the established GBM cell lines, KS4 and U87, revealed a strong repression of proliferation-associated genes, resulting in an enrichment of GO terms, including “Mitotic cell cycle,” “Nuclear division,” and “RB in cancer” (Fig. 6C Supplementary Fig. S5D). Interestingly, analysis of the genes upregulated by SOX5/6/21 instead resulted in a significant enrichment of GO terms associated with general tumor suppressor responses, including “Apoptotic process,” “Cellular response to stress,” “Direct p53 effector,” and “Senescence and Autophagy” (Fig. 6C Supplementary Fig. S5D).

SOX5/6/21 can restore tumor suppressor responses in human GBM cells. A, Deregulated genes in human primary GBM cells, KS4, after the transduction with SOX5-, SOX6-, or SOX21-expressing lentiviruses (n = 3). B, Gene overlap enrichment scores showing correlations of genes up- or downregulated in human primary GBM cells, KS4, after the transduction with SOX5-, SOX6-, or SOX21-expressing lentiviruses (n = 3). C, GO analysis on gene sets up- and downregulated in human primary GBM cells, KS4, transduced with SOX5/6/21-expressing lentiviruses. Significant GO terms are represented in the collapsed bars. D, Expression of p16, p21, p27, p57, and p53 in five human primary GBM cell samples and the glioma cell line U87 4 days after transduction with SOX5-, SOX6-, or SOX21-expressing lentiviruses. E and F, FACS-analysis of cell death 9 to 12 days after that GBM cells were transduced with SOX5/6/21 expressing lentiviruses. Quantification of total Annexin V labeling shown as fold change over GFP control (F n = 3). Q1, early apoptotic cells Q2, late apoptotic cells Q3, live cells Q4, necrotic cells. G, Expression of BIM, BID, BAX, BAK, and cleaved caspase-9 and -3 in SOX5/6/21–transduced human primary GBM cells (KS4). H and I, X-gal–based detection of cellular senescence in primary human GBM cells (#87) more than 3 days posttransduction with SOX5/6/21–expressing lentiviruses. Quantification of X-gal color intensity and area (I n = 8). Scale bars in H, 20 μm. For all graphs, data are shown as mean ± SEM. *, P < 0.05 **, P < 0.01 ***, P < 0.001.

Cellular defense mechanisms following oncogenic stress are mediated through the upregulation of CDK inhibitors and tumor suppressors, which results in the deceleration of cell-cycle progression, as well as induction of cellular senescence and apoptosis. Because p16, p21, p27, p57, and p53 are potent regulators of these cellular processes (4, 5, 43, 44), we assessed the expression levels of these proteins in cultured human primary GBM cells, 72 hours after the transduction with SOX5/6/21-expressing lentiviruses. As expected, both the primary GBM cells and the established GBM cell lines had undetectable, or only low levels of p16, p21, p27, p57, and p53 proteins (Fig. 6D). However, the levels of these proteins were significantly upregulated in the different cell lines in response to forced expression of SOX5/6/21 (Fig. 6D). Notably, even though their level of upregulation varied in a cell specific manner, cells transduced with SOX21-expressing lentiviruses exhibited the most abundant increase in the protein levels of p16, p21, p27, p57, and p53, compared to those cells overexpressing SOX5 or SOX6 (Fig. 6D).

Because the induction of apoptosis and cellular senescence has been attributed to the activity of CDK inhibitors and p53, we next examined these cellular processes in cultured human GBM cells after transduction with SOX5/6/21-expressing lentiviruses. In line with the upregulation of CDK inhibitors and p53, flow cytometry-based analysis of fluorochrome-labeled Annexin V levels revealed a significantly higher level of apoptosis in U87 cells, as well as, in the five primary GBM cell lines (KS4, G3, JM3, #87, and #89) overexpressing SOX5/6/21, compared to those cells transduced with GFP-expressing lentiviruses (Fig. 6E and F Supplementary Fig. S5E). Consistently, forced expression of SOX5/6/21 resulted in increased levels of the pro-apoptotic proteins BIM, BID, BAX, and BAK, together with upregulation of the active forms of CASPASE-9 and -3, indicating that SOX5/6/21 proteins induce apoptosis in these human primary GBM cells through permeabilization of the mitochondrial membrane (Fig. 6G Supplementary Fig. S5F refs. 45, 46). Furthermore, forced expression of SOX5/6/21 significantly increased the number of cells that entered senescence in the three human primary GBM cell lines (KS4, G3, and #87), as measured by senescence-associated βgal-activity (SA-βgal) and the cleavage of X-gal (Fig. 6H and I Supplementary Fig. S5G ref. 15).

SOX21 mediates tumor suppressor response by modulating p53 levels

Although the above findings provide evidence that increased levels of SOX5, SOX6, and in particular SOX21, are sufficient to restore tumor suppressor responses in human primary GBM cells, shRNA-mediated knockdown of p53 expression inhibited apoptosis and cellular senescence in response to forced SOX21 expression (Fig. 7A–E). The observation that the presence of p53 protein appears to be central for the capacity of SOX21 to facilitate a tumor suppressor response in GBM cells raises the question of how SOX21 promotes the increase in p53 levels. Notably, despite a robust increase in p53 protein levels upon forced SOX21 expression (Figs. 6D and 7A and B), a corresponding upregulation of TP53 gene expression could not be detected (Supplementary Fig. S6A). In fact, although the protein levels of CDK inhibitors (p16, p21, p27, p57) and p53 were increased in response to SOX21 overexpression (Figs. 6D and 7A and B), only CDKN1A (p21) and CDKN1C (p57) demonstrated a significant upregulation at the mRNA level (Supplementary Figs. S6B–S6E). Moreover, while CDKN1A expression is positively regulated by p53 protein (Fig. 7A and B Supplementary Fig. S6F ref. 44), the ability of SOX21 to upregulate the expression of CDKN1A was completely abolished in the presence of shRNA targeting TP53 (Supplementary Fig. S6G and S6H). Consistent with these findings, ChIP-seq–based binding studies of SOX21 in human primary GBM cells (KS4) failed to detect any SOX21 binding in the vicinity of the transcriptional start (<500 kilo base-pairs) of CDKN1A, -1B, -1C, -2A, or TP53 (Supplementary Fig. S6I Supplementary Table S3). Thus, the ability of SOX21 to upregulate p16, p27, and p53 appears mainly to be achieved at the protein level.

SOX21 decreases p53 protein turnover. A and B, p53 and p21 protein levels in human primary GBM cells, #87 (A) and KS4 cells (B), 4 days after the transduction with lentiviruses expressing SOX21, scrambled shRNAs or shRNAs targeting TP53 transcripts. C, Analysis of cell death of primary human GBM cells (KS4) 8 days after the misexpression of SOX21 with or without control shRNAs, or shRNAs targeting TP53 transcripts (n = 3). D, Expression of cleaved caspase-3 in human primary GBM cells (KS4) 8 days after the transduction with lentiviruses expressing SOX21, control shRNAs, or shRNAs targeting TP53 transcripts. E, Quantifications of X-gal–based detection of cellular senescence in human primary GBM cells (#87) as fold change over GFP control (n = 3). F and G, Cycloheximide (CHX)-based p53 protein turn-over assay in human primary GBM cells (#87 F) and U87 glioma cell line (G) 4 to 5 days posttransduction with control and SOX21 expressing lentiviruses. H and I, Expression of phosphorylated p53 (P-p53) in the human primary GBM cells #87 (H) and KS4 (I) transduced with SOX21 or control-expressing lentiviruses. J and K, Expression of MDM2 in human primary GBM cells (#87 J) and (KS4 K) transduced with SOX21 or control-expressing lentiviruses. L, Model of how Sox5/6/21 prevent oncogenic transformation. For all graphs, data are shown as mean ± SEM. *, P < 0.05 **, P < 0.01 ***, P < 0.001.

We next examined if SOX21-driven upregulation of p53 is achieved through an ability to stabilize this tumor suppressor on a protein level (47). Indeed, SOX21 markedly extended the half-life of p53 protein in human primary GBM cells (#87) and the glioma cell line U87 after protein synthesis inhibition by cycloheximide (Fig. 7F and G). SOX21 misexpression in these cells also resulted in the upregulation of phosphorylated (Ser15) p53, which is a stable form of this protein (Fig. 7H and I). Moreover, the level of the ubiquitin-protein ligase, MDM2, which is a negative regulator of p53 (48), was significantly reduced in GBM cells overexpressing SOX21 (Fig. 7J and K). However, SOX21 failed to downregulate MDM2 mRNA (Supplementary Fig. S6J) and neither could we detect any binding of SOX21 to the MDM2 gene (Supplementary Table S3). Together these data show that SOX21 can in part restore initiation of a tumor suppressor response in GBM cells by counteracting p53 protein turnover, possibly through the regulation of MDM2 protein levels (Fig. 7L).


Human Population

Human population refers to the number of people living in a particular area, from a village to the world as a whole. A secondary meaning of population is the inhabitants themselves, but in most uses population means numbers.

No one knows the population of the earliest humans, but there may have been only a few tens of thousands of individuals when the species Homo sapiens first emerged 200,000 years ago. Today more than 6 billion human beings inhabit the earth. Three-fifths of them live in one continent, Asia, with the rest occupying every continent except Antarctica.

The overwhelming bulk of human population growth has occurred since the Industrial Revolution began, more than half since 1950. All but a small percentage of the roughly 80 million people added to world population each year live in the world's developing countries, which are home to 80 percent of humanity and more than 95 percent of world population growth. In Europe and Japan, small average family size and relatively modest immigration levels are leading to a leveling of, and even decreases in, population. In the United States, Canada, and Australia, slightly larger families and higher levels of immigration make for continued population growth.

World population grows because births significantly outpace deaths on average. This imbalance occurs not because women are having more children than they once did—quite the reverse𠅋ut because improved sanitation and health mean that many more children than in the past survive to become parents themselves. Human reproduction is such a success story that some analysts believe that today's large and ever-increasing population growth threatens the earth's support systems and contributes to global poverty.

Debate on this question has raged since at least the 1800s. Some economists and other social scientists argue that higher populations provide more human resources for solving problems and producing wealth. Most physical and biological scientists, by contrast, argue that key natural resources𠅏resh water, cropland, forests, and fisheries, for example𠅊re increasingly strained by burgeoning human demands. Rising natural resource consumption by individuals also boosts these demands. The long-term growth of human population clearly has been an especially significant factor in human-induced climate change, species extinction, the loss of forests, and other environmental problems. But scientists and other analysts have been unable to agree on population's exact role in environmental change. Many other factors, from consumption patterns to government policies to the unequal distribution of power and wealth, also influence the environment.

One clear trend in human population is that its growth is slowing down. Women and men increasingly want to have later pregnancies and smaller families than did their own parents. Governments increasingly provide the health services that allow couples to plan their families. For some countries, this trend raises questions about how societies will cope with lower proportions of young and working people. For the world as a whole, however, births are likely to outnumber deaths for decades to come, and human population will continue to grow.


Age Structure, Population Growth, and Economic Development

The age structure of a population is an important factor in population dynamics. Age structure is the proportion of a population at different age ranges. Age structure allows better prediction of population growth, plus the ability to associate this growth with the level of economic development in the region. Countries with rapid growth have a pyramidal shape in their age structure diagrams, showing a preponderance of younger individuals, many of whom are of reproductive age or will be soon. This pattern is most often observed in underdeveloped countries where individuals do not live to old age because of less-than-optimal living conditions. Age structures of areas with slow growth, including developed countries such as the United States, still have a pyramidal structure, but with many fewer young and reproductive-aged individuals and a greater proportion of older individuals. Other developed countries, such as Italy, have zero population growth. The age structure of these populations is more conical, with an even greater percentage of middle-aged and older individuals. The actual growth rates in different countries are shown in Figure 4, with the highest rates tending to be in the less economically developed countries of Africa and Asia.

Art Connection

Figure 3: Typical age structure diagrams are shown. The rapid growth diagram narrows to a point, indicating that the number of individuals decreases rapidly with age. In the slow growth model, the number of individuals decreases steadily with age. Stable population diagrams are rounded on the top, showing that the number of individuals per age group decreases gradually, and then increases for the older part of the population.

Age structure diagrams for rapidly growing, slow growing and stable populations are shown in stages 1 through 3. What type of population change do you think stage 4 represents?

Figure 4: The percent growth rate of population in different countries is shown. Notice that the highest growth is occurring in less economically developed countries in Africa and Asia.


Population Distribution Definition

Population distribution is a term that is used to describe how people are spread across a specific area. In other words, population distribution shows where people live. Population distribution can be measured across the entire world or a smaller region within a country or continent. Population density is typically expressed as the number of persons per square kilometer (/km2) or square mile (mi2).

When looking at the world as a whole, the northern hemisphere has a much greater population than the southern hemisphere, which is home to less than 10% of the world’s total population. When looking further at the world’s total population distribution, nearly three-quarters of the population live in Africa and Asia.

Areas that are densely populated have very large populations within a unit of area. Areas that are sparsely populated have much smaller populations in a unit of area. Regions that are not densely populated generally have a hostile environment, including a lack of vegetation, extremely cold temperatures, and/or geographic isolation. Densely populated areas run the risk of higher costs of living, more traffic, depletion of resources, and more pollution.

The most densely populated regions, on the other hand, have more favorable climates, clean water, and an abundance of natural resources. This includes regions such as Western Europe or the Eastern United States. The most densely populated countries are Macau (21,055 persons per square kilometer), Monaco (19,150 persons per square kilometer), and Singapore (8,109 persons per square kilometer). The most densely populated city globally is Dhaka, Bangladesh, where the density is 44,000 per square kilometer. Mumbai, India, follows with 32,300 persons per square kilometer.

Population distribution is shown through a dot mop, with each dot on the map representing many people. This data can also be shown on choropleth maps, which use shading, coloring, and symbols to show population distribution.


Moving Toward a Sustainable Food Future

The challenge of feeding 10 billion people sustainably by 2050 is much harder than people realize. These menu items are not optional—the world must implement all 22 of them to close the food, land and GHG mitigation gaps.

The good news is that all five courses can close the gaps, while delivering co-benefits for farmers, society and human health. It will require a herculean effort and major changes to how we produce and consume food. So, let’s get started and order everything on the menu!

Download the full report, Creating a Sustainable Food Future, authored by Tim Searchinger, Richard Waite, Craig Hanson, Janet Ranganathan, Patrice Dumas and Emily Matthews

EDITOR'S NOTE, 4/15/19: In a previous version of the "Animal-based foods are more resource-intensive than plant-based foods" graphic, "rice" and "roots and tubers" were listed in the incorrect order. We have corrected the graphic, and we regret the error.


Author information

These authors contributed equally: Giorgia Maroni, Mahmoud A. Bassal, Indira Krishnan.

These authors jointly supervised this work: Azhar Ali, Daniel G. Tenen, Elena Levantini.

Affiliations

Cancer Science Institute of Singapore, National University of Singapore, Singapore, Singapore

Giorgia Maroni, Mahmoud A. Bassal, Chee Wai Fhu, Jia Li, Henry Yang, Azhar Ali & Daniel G. Tenen

Harvard Medical School, Boston, MA, USA

Giorgia Maroni, Mahmoud A. Bassal, Indira Krishnan, Junyan Zhang, Riccardo Panella, Assunta De Rienzo, Olivier Kocher, Raphael Bueno, John G. Clohessy, Daniel G. Tenen & Elena Levantini

Institute of Biomedical Technologies, National Research Council (CNR), Area della Ricerca di Pisa, Pisa, Italy

Giorgia Maroni, Maria Cristina Magli & Elena Levantini

Department of Systems Biology, Harvard Medical School, Boston, MA, USA

Virginia Savova, Rapolas Zilionis & Allon M. Klein

Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania

Beth Israel Deaconess Medical Center, Boston, MA, USA

Valerie A. Maymi, Nicole Pandell, Eva Csizmadia, Olivier Kocher, John G. Clohessy & Elena Levantini

Preclinical Murine Pharmacogenetics Core, Beth Israel Deaconess Cancer Center, Dana Farber/Harvard Cancer Center, Boston, MA, USA

Valerie A. Maymi, Nicole Pandell & John G. Clohessy

NEST, Scuola Normale Superiore and Istituto Nanoscienze-CNR, Pisa, Italy

Barbara Storti & Ranieri Bizzarri

Platform for Immunotherapy BST-Hospital Clinic, Banc de Sang i Teixits (BST), Barcelona, Spain

Center for Genomic Medicine, Desert Research Institute, Reno, NV, USA

Division of Thoracic Surgery, The Lung Center and the International Mesothelioma Program, Brigham and Women’s Hospital, Boston, MA, USA

Corinne E. Gustafson, Sam Fox, Rachel D. Levy, Claire V. Meyerovitz, Peter J. Tramontozzi, Kimberly Vermilya, Assunta De Rienzo & Raphael Bueno

Unit of Clinical Pharmacology and Pharmacogenetics, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy

Stefania Crucitta & Romano Danesi

Biochemistry Department, Chemistry Institute, University of Sao Paulo, Sao Paulo, Brazil

PTC Therapeutics, 100 Corporate Court, South Plainfield, NJ, USA

Marla Weetall & Art Branstrom

Cell Biology Unit, Department of Pathology and Experimental Therapeutics, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain

Stem Cell Biology and Leukemiogenesis Group, Regenerative Medicine Program, Institut d’Investigació Biomèdica de Bellvitge - IDIBELL, L’Hospitalet de Llobregat, Barcelona, Spain

Endocrine Unit, Department of Clinical and Experimental Medicine, University Hospital of Pisa, Pisa, Italy

Unit of Clinical Pharmacology and Pharmacogenetics, Department of Laboratory Medicine, University Hospital of Pisa, Pisa, Italy

Department of Surgical, Medical and Molecular Pathology, and Critical Care Medicine, University of Pisa, Pisa, Italy

University of Alabama at Birmingham, Department of Medicine, Hemathology/Oncology, Birmingham, AL, USA

Harvard Stem Cell Institute, Cambridge, MA, USA

Daniel G. Tenen & Elena Levantini

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Contributions

E.L., D.G.T., A.A., G.M., I.K., and M.A.B. designed the study E.L., A.A., G.M., I.K., M.A.B., J.C., D.S.B., A.G., M.D.R., RB, R.S.W., and J.G.C. performed and planned research E.L., D.G.T., A.A., G.M., I.K., M.A.B., V.S., R.Z., B.S., J.C., R.P., J.L., D.S.B., M.W., A.B., A.G., R.C., M.D.R., R.D., R.B., H.Y., O.K., M.C.M., R.S.W., A.M.K., R.B., and J.G.C. analyzed data F.C.W., V.S., R.Z., V.A.M., N.P., E.C., J.Z., C.E.G, S.F., R.D.L., C.V.M., P.J.T., K.V., A.D.R., S.C., and R.C. performed research and E.L., D.G.T., A.A., G.M., I.K., and M.A.B. wrote the paper.

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Watch the video: Biology Human Population Growth (August 2022).